Antigen discovery for t cell receptors isolated from patient tumors that recognize wild-type antigens and potent peptide mimotopes

Abstract

To provide high throughput and highly sensitive approaches for determining the specificity of TCR of unknown antigen specificity that could help uncover potential targets for cancer immunotherapy, autoimmunity and infection and provide mechanistic insight into disease pathogenesis.SOLUTION: A composition and a method are provided for a peptide sequence being a ligand for a T cell receptor (TCR) of interest in a defined MHC context. The composition may comprise or consist of a defined peptide, or may comprise or consist of a polynucleotide encoding such a peptide. Such peptides may be fragments of naturally occurring antigenic proteins; may be fragments of neoantigenic proteins that are the subject of somatic mutation during tumorigenesis, or may be a synthetically generated analog of an antigenic protein.SELECTED DRAWING: Figure 1-1

Description

[Background technology]

[0001] T cells are essential to the adaptive immune system, providing protection against pathogens and cancer. They function through extracellular recognition by TCRs that are specific for short peptides presented on human leukocyte antigens (HLA) on cells (Birnbaum et al., (2014) Cell 157, 1073-1087). The inherent diversity of TCRs, peptides, and HLA molecules makes identifying the specificity of any one TCR an extremely complex problem.

[0002] Although our ability to characterize T cells and sequence their TCRs has improved considerably in recent years (Han et al., (2014) Nat Biotechnol 32, 684-692; Stubbington et al., (2016) Nat Methods 13, 329-332), our ability to determine and interrogate the antigen specificity of T cells has not progressed similarly.

[0003] Each human individual is 7 ~10 8 10 in their bodies, along with the species' unique T cell receptors 12 Each T cell expresses a unique T cell receptor (TCR) that is selected for its ability to bind peptide-presenting major histocompatibility complex (MHC) molecules. TCR recognition of peptide-MHC (pMHC) drives T cell development, survival, and effector function. Even though the TCR ligands are of relatively low affinity (1-100 μM), the TCR is highly sensitive, requiring as few as 10 agonist peptides to fully activate a T cell. After recognition, a signaling cascade enables T cells to perform their immune functions.

[0004] Extensive structural investigations of TCR recognition of pMHC have shown that the vast majority of TCR-pMHC complexes examined share a consistent binding orientation driven by conserved contacts between the tops of the MHC helices and the germline-encoded TCR CDR1 and CDR2 loops (see Garcia and Adams (2005) Cell 122, 333-336, Garcia et al. (2009) Nat Immunol 10, 143-147, and Rudolph et al. (2006) Annual Review of Immunology 24, 419-466). These conserved contacts have likely co-evolved throughout the development of the adaptive immune system and serve as the basis for MHC restriction of the αβTCR repertoire (Scott-Browne et al., 2011). Alterations in canonical TCR-pMHC interactions have been shown to correlate with ineffective signaling and, when present during development, skewed TCR repertoires (Adams et al. (2011) Immunity 35(5):681-93; Birnbaum et al. (2012) Immunol. Rev. 250(1):82-101).

[0005] An additional important feature of TCRs is their ability to balance cross-reactivity and specificity. Because the number of T cells required to uniquely recognize every possible pMHC combination is extremely high, and because few, if any, "holes" are characterized in the TCR repertoire, a significant degree of TCR cross-reactivity has been postulated as a requirement for functional antigen recognition. How a T cell repertoire can simultaneously be MHC-restricted and cross-reactive enough to ensure that all potential antigen challenges can be met, yet still be specific enough to avoid pathological autoimmunity remains an open and pressing question in immunology.

[0006] There are several strategies used to determine the specificity of orphan TCRs (Birnbaum et al., (2012) Immunol Rev 250, 82-101). Mass spectrometry can provide an unbiased method of antigen isolation, but typically requires 10 7 ~10 9 This is limited to experiments that require large cell numbers of up to 1000 cells, and the target must still be presented by the correct HLA. Traditionally, most investigations of T cell antigen specificity have involved empirically testing candidate antigens. For example, investigations of anti-tumor T cell specificity correctly assume that there will be a productive T cell response against the neoantigen. Such investigations involve sequencing the tumor to identify mutations, using epitope prediction algorithms to predict immunogenic variant peptides, and testing for T cell responses directed against these variant peptides (Kreiter et al., 2003). al., (2015) Nature 520, 692-696; Rajasagi et al., (2014) Blood 124, 453-462; Tran et al., (2014) Science 344, 641-645). Another strategy uses pHLA multimers to interrogate established T cell specificities in patients (Bentzen et al., (2016) Nat Biotechnol 34, 1037-1045; Newell et al., (2013) Nat Biotechnol 31, 623-629).

[0007] High-throughput and sensitive methods to determine the specificity of "orphan" TCRs (i.e., TCRs of unknown antigen specificity) are of great interest, which could help reveal potential targets for cancer immunotherapy, autoimmunity, and infectious diseases and provide mechanistic insights into disease pathogenesis. Summary of the Invention

[0008] Compositions are provided for ligands for a T cell receptor (TCR) of interest in a defined MHC context. The compositions may comprise or consist of a defined peptide, or may comprise or consist of a polynucleotide encoding such a peptide. Such peptides may be fragments of naturally occurring antigenic proteins, fragments of neoantigen proteins that are subject to somatic mutation during tumorigenesis, or synthetically generated mimics of antigenic proteins. Synthetic peptides may act as highly potent agonists of T cell receptors. In some embodiments, the peptide or coding sequence is selected from the sequences provided herein, including, but not limited to, any one or combination of the peptide sequences set forth in SEQ ID NOs: 1-257. The peptides may be provided as short antigenic sequences that are active in stimulating T cells, or may be provided in the form of larger proteins, such as intact domains, soluble protein portions, complete proteins, etc. In some embodiments, peptide antigens are identified that are shared among patients and provide a means for broadly applicable therapy. In other embodiments, the identification of antigens provides a personalized medicine approach.

[0009] Identification of T cell receptors and cognate antigens provides targets for immunotherapy, including screening patient T cells for responsiveness, vaccination with peptides or nucleic acids encoding such peptides, cell-based therapies, protein-based therapies, etc. The peptides and methods disclosed herein are useful in classifying TCRs based on peptide antigen specificity, allowing the identification of clinical candidate TCRs that recognize antigens shared across patients.

[0010] In some embodiments, a method for vaccination against cancer, e.g., colorectal cancer, is provided, the method comprising administering an effective dose of a vaccine composition, the composition comprising a peptide identified herein, a combination of peptides, e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10 or more individual peptides, a peptide and a MH The vaccine may comprise a complex with at least a portion of the C protein, an autologous or allogeneic T cell stimulated to respond to the antigenic peptide identified herein, a nucleic acid encoding the antigenic peptide identified herein, and optionally a pharma- ceutically acceptable excipient that may include a vaccine adjuvant. Using a peptide vaccination strategy, the immune response may be initially primed with, for example, a synthetic peptide provided herein, followed by a boost with the corresponding known wild-type antigen or wild-type whole protein.

[0011] Defined peptides are identified by screening peptide-MHC libraries by yeast display, which is used to identify the recognition shape of individual T cell receptors. The screening method can be utilized in a multiplexed method to simultaneously screen multiple peptide libraries, e.g., 2, 3, 4 or more libraries. Multiplexing allows for improved efficiency of antigen discovery. Each library can contain a unique epitope tag that allows for identification, e.g., an epitope targetable by an antibody, and can include DNA barcodes, protein barcodes, etc. Each library utilizing epitope tags was created separately, and diversity was calculated based on colony counts, e.g., from limiting dilution of the initial library on a growth plate. Selections, e.g., peptide sequences, peptide lengths, collections of various MHC or HLA alleles, etc., can be further multiplexed by pooling T cell receptors for library selection. For selection, each barcode, epitope tag, etc. can be monitored via anti-epitope tag staining to detect the level of peptide-specific enrichment. Statistical and machine learning algorithms can be used for identification.

[0012] In some embodiments, sequences of T cell receptors responsive to cancer antigens are provided. The T cell receptor sequences may include, but are not limited to, proteins having an alpha chain with the sequence set forth in SEQ ID NO:258, optionally combined with a beta chain sequence of SEQ ID NO:259 or SEQ ID NO:260. The binding region (CDR) sequences of these T cell receptors may be grafted onto antibody frameworks to provide TCR-like antibodies. Since T cell receptors are flexible and often unique to each patient, individual T cell receptor sequences may vary between patients. Despite these differences, different TCRs may still recognize the same target. Thus, different T cell receptors may have slight sequence variations from these T cell receptors that may bind to the same target. In addition, T cell receptors may be modified to introduce amino acid substitutions that allow binding to the same antigen. Such cases include affinity maturation of T cell receptors to specific targets, or receptor modifications that improve the specificity of T cell receptors to their targets. The recognition portion of the T cell receptor may be grafted onto other protein scaffolds of interest for use as therapeutic reagents. The list of synthetic peptides is not exhaustive, as T cell receptors are somewhat cross-reactive, and slight modifications of the peptide sequence may still result in T cell stimulation.

[0013] In some embodiments, the T cells from which the TCR sequences for screening are obtained are isolated from the tumor site and may include, but are not limited to, tumor infiltrating T cells (TILs). In other embodiments, the T cells are obtained from an individual who is responsive to an infection, e.g., a bacterial, viral, protozoan, etc. infection. In other embodiments, the T cells may be obtained from a graft recipient and isolated from the site of the graft.

[0014] The invention is best understood from the following detailed description when read in conjunction with the accompanying drawings. The patent or application file contains at least one drawing illustrated in color. According to common practice, the various features of the drawings are not drawn to scale. On the contrary, dimensions of the various features have been arbitrarily expanded or reduced for clarity. The following figures are included in the drawings: [Brief description of the drawings]

[0015] [Figure 1-1] The design of the peptide-HLA-A*02:01 yeast display library is shown. In A, the methodology for selecting the pHLA yeast display library is shown. Each yeast displays a unique peptide that is genetically encoded. A typical library contains approximately 108 unique peptides that are selected by the TCR of interest. The yeast is enriched in affinity-based selection using bead-multimerized TCRs and grown for repeated rounds of selection. Peptides are sequentially enriched and the total yeast DNA is deep sequenced. These synthetic peptide sequences are used to create models that predict for TCR ligands derived from the human proteome and / or patient-specific exomes. In B, the goal of the investigation is to deorphanize TCRs of unknown antigen specificity using yeast display selection. The peptides selected by the TCR from the yeast display selection create recognition shapes for specific TCRs that are then used to predict antigen specificity for orphan TCRs. The predicted targets can be validated in T cell stimulation assays. In C, the construct utilizes a single-chain design to display the pHLA-A* 02:01 complex tethered to an epitope tag and Aga2p, which binds to the native Aga1 protein on yeast. Each component is covalently linked by a Gly-Ser linker. The epitope tag is introduced to monitor the expression of the library. In D, the MART-1 / HLA-A* 02 complex structure (PDB 4L3E) is shown with orange arrows highlighting the two peptide anchors. These peptide sites at P2 and PΩ of the peptide allow for peptide binding to HLA-A* 02. [Figure 1-2] The peptide-HLA-A* 02:01 yeast display library design is shown. In E, an example 8mer peptide library shows the anchor preference for the HLA-A* 02:01 library and the remaining positions randomized to one of 20 amino acids (X = 20 amino acids and a stop codon). Nucleotide abbreviations for codon usage are written according to the IUPAC nucleotide code. In F, a multi-length library designed to capture the most common peptide lengths presented by HLA-A* 02:01 is shown. Each peptide length is placed in a construct with a unique epitope tag for selection monitoring. The library has a theoretical nucleotide diversity dictated by peptide length and library composition. Functional diversity represents the true capacity of the physical library based on yeast colony counts after limiting dilution of the library. [Diagram 2]Validation of HLA-A* 02:01 library with DMF5 TCR. In A, DMF5 TCR lineage yeast displaying MART-1 peptide (ELAGIGILTV) (SEQ ID NO:264) in complex with HLA-A* 02:01 on the surface of yeast is shown. Streptavidin-647 (SA-647) was used to tetramerize and fluorescently label the DMF5 TCR. In B, enrichment of 10-mer long HLA-A* 02:01 yeast display library with DMF5 TCR as measured by anti-HA epitope tag staining by flow cytometry is shown. Three out of four rounds of selection are shown. In C, highly enriched peptides sequenced from 10-mer selection with DMF5 TCR are stained with DMF5 TCR tetramer and measured by flow cytometry. (Sequences from left to right in C: SEQ ID NO: 264, 324, 286, 323, 283, 285). In D, the percentage of total sequencing read counts of the top 10 peptides following deep sequencing of round 3 of 10mer HLA-A*02:01 library selection with DMF5 TCR is shown. (Sequences from top to bottom in D: SEQ ID NO: 287, 326, 325, 324, 286, 323, 285, 322, 284, 283). In E, the unique peptides from round 3 of selection fall into two major clusters that appear similar to the wild type MART-1 peptide sequence (SEQ ID NO: 267). The clusters are determined by first calculating the inverse Hamming distance between all peptides present in round 3 of selection and then clustering by score. The MART-1 decamer structure (PDB: 4L3E) is aligned to the selected peptides. In F, the substitution matrix (2014PWM) using the cluster 1 peptide predicts the MART-1 peptide as the most likely peptide to bind to the DMF5 TCR among the other 8 predicted peptides. (Sequence from top to bottom in F: SEQ ID NOs: 321, 320, 319, 318, 317, 316, 315, 314, 267). [Figure 3-1]Blind validation of the HLA-A* 02:01 library with neoantigen-specific TCRs. In A, three TCRs of blind specificity separately enrich the HLA-A* 02:01 library for specific peptide lengths, followed by epitope tag staining across rounds of selection. The left panel shows tetramer and epitope staining after all four rounds of selection have been completed, and the right panel shows epitope staining throughout the selection process. [Figure 3-2] Blind validation of the HLA-A* 02:01 library with neoantigen-specific TCRs. In B, the unique peptides selected by NKI2 in round 3 of selection are analyzed by peptide length and clustered by inverse Hamming distance. The number of peptides identified in a cluster is shown on the right along with the respective peptide length. [Figure 3-3] Blind validation of HLA-A*02:01 library with neoantigen-specific TCR. In C, the maximum inverse Hamming distance calculated between every 10-mer of peptides selected by NKI2 in round 3 and each 10-mer neoantigen peptide from the list of all 127 neoantigens is shown. (Sequence from top to bottom in C: SEQ ID NO: 501, 502, 620, 503-519). In D, two peptides from the selected library, Lib-1 (SEQ ID NO: 434) and Lib-2 (SEQ ID NO: 269), closely resemble the 10-mer neoantigen peptide ALDPHSGHFV (SEQ ID NO: 265) derived from CDK4. Amino acids identical to the neoantigen are colored red. In E, the top 5 peptides of length 10 selected by NKI2 TCR were used to stimulate peripheral blood lymphocytes transduced to express TCRs NKI1 or NKI2, both specific for CDK4 neoantigen ALDPHSGHFV (SEQ ID NO: 265). Transduced lymphocytes were mixed 1:1 with JY cells pulsed with peptide, control peptide, or no peptide, and IFNγ production, as measured by intracellular antibody staining, was assessed using flow cytometry. (Sequences from top to bottom in E: 1) SEQ ID NO:269, 2) SEQ ID NO:427, 3) SEQ ID NO:423, 4) SEQ ID NO:420, 5) SEQ ID NO:417). [Figure 4-1] Profiling of TCRs identified in two HLA-A*02 patients with colorectal adenocarcinoma. In A, the study design for deorphanizing patient-derived TCRs with the HLA-A*02:01 library is shown with summarized results. In B, a bar graph of the abundance of unique paired αβTCR sequences from TILs is shown. *=TCR enriched with peptides from the library. [Figure 4-2] Figure 1 shows the profiling of TCRs identified in two HLA-A*02 patients with colorectal adenocarcinoma. In C, a Venn diagram is shown depicting the overlap of individual unique CDR3α or CDR3β chain sequences between tumor and healthy tissue for each patient. The numbers indicate the amount of CDR3 sequences in the nearest area of ​​the Venn diagram. In D, a heat map is shown in which a binary measure of transcription factors was identified using sequencing of amplified and barcoded transcripts. Alternating black and white panels indicate the boundaries of single T cell clones with the same receptor sequence, with the most abundant clone starting at the far left. The left panel identifies those T cells with a selected TCR from patient A to be screened, green indicates the presence of the transcript. The right panel identifies those T cells with a selected TCR from patient B to be screened, blue indicates the presence of the transcript. White indicates the absence of the transcript detected. TCRs 1A, 2A, 3B, and 4B are labeled. [Figure 5-1]Four TIL-derived TCRs are shown to enrich the HLA-A* 02:01 library for peptides. In A, the TCR sequences of four orphan TCRs that selected peptides from the HLA-A* 02:01 library are shown. TCR gene segment variables and junctions are shown with the corresponding CDR3 sequences. Abundance represents the amount of times a single cell was found to have the exact TCR sequence in tumor / healthy tissue. (Sequences in A: 1A CDR3α: (SEQ ID NO: 472), 2A CDR3α: (SEQ ID NO: 261), 3B CDR3α: (SEQ ID NO: 261), 4B CDR3α: (SEQ ID NO: 495), 1A CDR3β: (SEQ ID NO: 463), 2A CDR3β: (SEQ ID NO: 262), 3B CDR3β: (SEQ ID NO: 263), 4B CDR3β: (SEQ ID NO: 484)). In B, the nucleotide sequences of two sequence-similar TCRs isolated from patients A and B are shown. Non-coding nucleotides are highlighted in red. (Amino acid sequences in B: CDR3α 2A: (SEQ ID NO: 261), CDR3α 3B: (SEQ ID NO: 261), CDR3β 2A: (SEQ ID NO: 262), CDR3β 3B: (SEQ ID NO: 263)); Nucleotide sequences: CDR3α 2A nucleotide sequence: (SEQ ID NO: 536), CDR3α 3B nucleotide sequence: (SEQ ID NO: 537), CDR3β 2A nucleotide sequence: (SEQ ID NO: 538), CDR3β 3B nucleotide sequence: (SEQ ID NO: 539). [Figure 5-2] Four TIL-derived TCRs enrich the HLA-A* 02:01 library for peptides. In C, HLA enrichment and tetramer staining per round of selection with the four orphan TCRs as measured by flow cytometry. The left panel shows tetramer and epitope staining after all four rounds of selection have been completed, and the right panel shows epitope staining throughout the course of selection. [Figure 5-3]Four TIL-derived TCRs enrich the HLA-A* 02:01 library for peptides. In C (cont.), HLA enrichment and tetramer staining per round of selection with the four orphan TCRs as measured by flow cytometry. The left panel shows tetramer and epitope staining after all four rounds of selection were completed, and the right panel shows epitope staining throughout the selection process. [Figure 6] Deep sequencing results of yeast selection with four TIL TCRs are shown. In A, word logos represent unique peptides selected in round 3 for each TCR and do not account for deep sequencing read count abundance. The size of the amino acid letter represents its proportional abundance at a given position among unique peptides. In B, heat map plots showing amino acid composition per peptide position illustrating peptide enrichment in round 3 of selection. Darker colors indicate greater abundance of a given amino acid at a given position. Anchor residues are outlined in black. In C, TCRs 2A and 3B select an overlapping set of 11 peptides in round 3 of selection shown as a percentage of total reads in round 3. (Sequence from top to bottom in C: SEQ ID NOs: 95, 249, 54, 195, 42, 191, 196, 198, 200, 201, 4). [Figure 7-1]Activation of TIL TCR with predicted human targets and peptide mimotopes. TCRs are retrovirally infected into CD8+ SKW-3 cells and sorted for stable TCR (IP26) and CD3 (UCHT1) co-expression. T2 antigen presenting cells are pulsed with 100 μM peptide for 3 h, co-incubated with T cell lines for 18 h and analyzed for CD69 expression by flow cytometry. TCR1A (A) and TCR2A (C) were tested in technical triplicates for CD69 activation by peptide stimulation and standard deviations are shown. A representative experiment from biological triplicates is shown. (Sequences from left to right in A: SEQ ID NO: 540-555, in C: SEQ ID NO: 556-574). In B, D, dose response curves for each stimulatory peptide are shown on the right, plotting the mean of the biological triplicates with the standard error of the mean. For both experiments, p-values ​​were calculated using ordinary one-way ANOVA. For TCR2A and 3B, 17 non-stimulatory peptides have been removed for simplicity (sequences from top to bottom in B: SEQ ID NOs: 540-543, sequences from top to bottom in D: 556-558, 560, 562-567). [Figure 7-2]Activation of TIL TCR with predicted human targets and peptide mimotopes. TCRs are retrovirally infected into CD8+ SKW-3 cells and sorted for stable TCR (IP26) and CD3 (UCHT1) co-expression. T2 antigen presenting cells are pulsed with 100 μM peptide for 3 h, co-incubated with T cell lines for 18 h and analyzed for CD69 expression by flow cytometry. TCR3B (E) and TCR4B (G) were tested in technical triplicates for CD69 activation by peptide stimulation and standard deviations are shown. A representative experiment from biological triplicates is shown. (Sequences from left to right in E: SEQ ID NO: 556-574, in G: SEQ ID NO: 596-619). In F,H, dose response curves for each stimulatory peptide are shown on the right, plotting the mean of the biological triplicates with the standard error of the mean. For both experiments, p-values ​​were calculated using ordinary one-way ANOVA. For TCR2A and 3B, 17 non-stimulatory peptides have been removed for simplicity. (Sequences from top to bottom in F: SEQ ID NOs: 41, 42, 193, 194, 195, 257; Sequences from top to bottom in H: 596-602, 604, 608, 610, 613, 615). [Figure 8] Validation of HLA-A2*01 library with DMF5 TCR. In A, MA2.1 antibody staining of correctly folded HLA-A*02:01 complex with DMF5 TCR wild type peptide or peptide mimotope. Histogram shows staining with MA2.1 antibody followed by secondary antibody. (Sequence from left to right in A: SEQ ID NO: 264, 324, 286, 323, 283, 285). In B, predicted human peptide scores using 2014 PWM algorithm on cluster 2 of round 3 sequences for DMF5 TCR 10mer selection. In C, scores of top 10 peptides identified in 8B. (Sequence from top to bottom in C: SEQ ID NO: 364, 363, 362, 361, 360, 359, 358, 357, 356, 355). [Figure 9-1]Patient tissue immunohistochemistry, as well as sequencing and phenotyping of the TCR repertoire are shown. In A, patient immunohistochemistry using H&E staining, anti-CD4 / hematoxylin, or anti-CD8 / hematoxylin is shown. All representative images are taken using 300x magnification. In B, the length of the patient CDR3 measured from Cys to Phe is shown. [Figure 9-2] Patient tissue immunohistochemistry as well as sequencing and phenotyping of the TCR repertoire are shown. In C, patient distribution of TCR variable alpha genes in healthy and tumor tissues is shown. [Figure 9-3] Patient tissue immunohistochemistry, as well as sequencing and phenotyping of the TCR repertoire are shown. In D, patient distribution of TCR variable β genes in healthy and tumor tissues is shown. [Figure 9-4] Patient tissue immunohistochemistry, as well as sequencing and phenotyping of the TCR repertoire are shown. In E, transcriptional profiling by transcript sequencing is shown (t-SNE plot of patient BT cells (left) and t-SNE plot of cell surface markers by flow cytometry (right)). Transcript presence is binary (1=yes, 0=no) based on deep sequencing reads and intensity is related to the MFI of the cell surface marker. [Figure 10]Design of machine learning algorithm 2017DL predicts human peptide specificity. A is a schematic diagram showing the process of taking data from yeast display library selection and training a machine learning model that scores peptides derived from proteins from the Uniprot database or patient-specific exomes. The model is generated from yeast display selection data using deep sequencing round counts per peptide and the composition of the peptides. An exponential curve is fitted to each peptide to capture the enrichment over the rounds of selection using a fitness function. B shows a fitness function for fitting the exponential curve to the deep sequencing round counts for peptides selected by the TCR. C shows a matrix representation of an example peptide where each amino acid is represented as a one-hot vector. D shows the architecture of the machine learning algorithm using a two-layer convolutional neural network. The input consists of the peptide sequence represented as a vector of one-hot vectors and the fitness score of the peptide determined from the fitness function. The output is the fitness score. [Figure 11-1] Activation of SKW-3 cells according to median CD69 MFI and TCR tetramer staining of yeast expressing predicted peptide targets is shown. Data from FIG. 7 are analyzed, but for A and B, the mean fluorescence intensity of CD69 expression is used instead of the percentage of cells positive for CD69 expression. SKW-3 T cells with TCR (A) 1A or (B) 2A were co-cultured with peptide-pulsed T2 antigen-presenting cells as in FIG. 7. Mean fluorescence intensity was measured in technical triplicates from anti-CD69 staining of CD3-gated SKW-3 cells, and the mean and standard deviation are shown. A representative experiment from biological triplicates is shown. p-values ​​were determined using ordinary one-way ANOVA. (Sequence from top to bottom in A: SEQ ID NO: 540-542) [Figure 11-2]Activation of SKW-3 cells according to median CD69 MFI and TCR tetramer staining of yeast expressing predicted peptide targets is shown. Data from FIG. 7 are analyzed, but for C and D the mean fluorescence intensity of CD69 expression is used instead of the percentage of cells positive for CD69 expression. SKW-3 T cells bearing TCR (C)3B or (D)4B were co-cultured with peptide-pulsed T2 antigen-presenting cells as in FIG. 7. Mean fluorescence intensity was measured in technical triplicates from anti-CD69 staining of CD3-gated SKW-3 cells, and the mean and standard deviation are shown. A representative experiment from biological triplicates is shown. p values ​​were determined using ordinary one-way ANOVA. [Figure 11-3] Activation of SKW-3 cells according to median CD69 MFI and TCR tetramer staining of yeast expressing predicted peptide targets. Yeast expressing library peptides against TCR (E)1A and (F)2A and single chain trimers of predicted target peptides were stained with 400 nM TCR tetramer. The tetramer negative population is stained with streptavidin-647 only. All yeast are gated on epitope tag positive yeast. [Figure 11-4] Activation of SKW-3 cells according to median CD69 MFI and TCR tetramer staining of yeast expressing predicted peptide targets. Yeast expressing library peptides against TCR (G)3B and (H)4B and single chain trimers of predicted target peptides were stained with 400 nM TCR tetramer. The tetramer negative population is stained with streptavidin-647 only. All yeast are gated on epitope tag positive yeast. [Figure 12-1]U2AF2 quantitative RNA expression and affinity measurements for U2AF2 peptide are shown. In A, quantitative PCR expression of U2AF2 transcript expression in tumors compared to healthy tissues in patients A and B, using 18S as a housekeeping gene. Samples were done in technical quadruplicate and standard deviations are shown. In B, log base 2 quantitative PCR expression of U2AF2 RNA in various human derived tumors compared to U2AF2 RNA expression in patient A healthy tissue, using 18S as a housekeeping gene. Samples were done in technical quadruplicate and standard deviations are shown. The cell lines shown are listed in the Methods section in the appropriate order. [Figure 12-2] U2AF2 quantitative RNA expression and affinity measurements for U2AF2 peptide are shown. In C, log base 2 quantitative PCR expression for U2AF2 RNA in various human derived tumors compared to U2AF2 RNA expression in patient B healthy tissues using 18S as housekeeping gene. Samples were done in technical quadruplicate and standard deviations are shown. Cell lines shown are listed in the Methods section in appropriate order. In D, surface plasmon resonance traces for increasing concentrations of TCR2A flowing over a chip coated with MMDFFNAQM-HLA-A* 02:01 (SEQ ID NO: 266) ranging from 93.6 μM to 0.365 μM using 2-fold dilutions. Peaks before and after TCR engagement to peptide-HLA-A* 02 resulting from flow cell subtraction have been removed for simplicity. Kd is calculated using only the colored curves with labeled concentrations. In E, a curve fit to the data points generated at various concentrations of labeled TCR in FIG. 4D is shown. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] Before further describing the invention, it should be understood that the invention is not limited to the specific embodiments of the invention described below, as variations of the specific embodiments may be made and still fall within the scope of the appended claims. It should also be understood that the terminology employed is for the purpose of describing the specific embodiments and is not intended to be limiting. In this specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise.

[0017] When a range of values ​​is provided, it is understood that each intervening value between the upper and lower limit of that range, to one-tenth of the unit of the lower limit unless the context clearly dictates otherwise, and any other stated or intervening value in that stated range, is encompassed within the invention. The upper and lower limits of these smaller ranges may be independently included in the smaller ranges and are also encompassed within the invention, subject to any limit specifically excluded in the stated range. When a stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the invention.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods, devices, and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, exemplary methods, devices, and materials are described herein.

[0019] All publications mentioned in this specification are incorporated herein by reference for the purpose of describing and disclosing the subject matter of the invention that is described in the publications, which may be used in connection with the invention described below.

[0020] The present invention has been described in terms of specific embodiments found or proposed by the inventors to include preferred modes for practicing the invention. In light of this disclosure, it will be understood by those skilled in the art that numerous modifications and changes can be made in the specific embodiments exemplified without departing from the intended scope of the invention. For example, due to codon redundancy, changes can be made in the underlying DNA sequence without affecting the protein sequence. Furthermore, due to biological functional equivalence considerations, changes can be made in the protein structure without affecting the biological action in kind or amount. All such modifications are intended to be included within the scope of the appended claims.

[0021] Screening method. Antigen sequences were discovered by creating a library of single-chain polypeptides containing the binding domain of a major histocompatibility complex protein and a variety of peptide ligands. The library is introduced into a suitable host cell, including but not limited to yeast cells, that expresses the encoded polypeptides. The TCR of interest is multimerized to enhance binding and is used to select host cells expressing such single-chain polypeptides that bind to the T cell receptor. Repeated rounds of selection are performed until the selected population has a signal above background, i.e., the cells selected in the first round provide the starting population for the second round, and so on, usually for at least three rounds and more usually for at least four rounds of selection. Single-chain polypeptides Polynucleotides encoding the final selected population from the library of peptides are subjected to high throughput sequencing. The selected set of peptide ligands exhibits a restricted selection of amino acids at residues, e.g., residues that contact the TCR, and this information can be input into an algorithm that can be used to analyze public databases for all peptides that meet the binding criteria, which provides a set of peptides that meet these criteria.

[0022] The peptide ligands are about 8 to about 20 amino acids in length, usually about 8 to about 18 amino acids, about 8 to about 16 amino acids, about 8 to about 14 amino acids, about 8 to about 12 amino acids, about 10 to about 14 amino acids, about 10 to about 12 amino acids. It is understood that a completely random library would result in a vast number of possible combinations. In a preferred method, the diversity is limited in the residues that anchor the peptide to the MHC binding domain, which are referred to herein as MHC anchor residues. The location of the anchor residues on the peptide is determined by the specific MHC binding domain. Class I binding domains may have anchor residues at P2 and at the last contact residue. Class II binding domains have anchor residues at P1 and one of P4, P6, or P9 depending on the allele. For example, IE k The anchor residues for HLA-DR15 are P1{I, L, V} and P4{F, Y}. The anchor residues for the DR alleles are shared at P1, with allele-specific anchor residues at P4, P6, P7, and / or P9.

[0023] In some embodiments, the binding domains of the major histocompatibility complex proteins are soluble domains of class II alpha and beta chains. In some such embodiments, the binding domains are subjected to mutagenesis to select for amino acid changes that enhance the solubility of the single chain polypeptide without altering the peptide binding contacts. In certain specific embodiments, the binding domains are HLA-DR4α, which comprises the set of amino acid changes {M36L, V132M}, and HLA-DR4β, which comprises the set of amino acid changes {H62N, D72E}. In certain specific embodiments, the binding domains are HLA-DR15α, which comprises the set of amino acid changes {F12S, M23K}, and HLA-DR15β, which comprises the amino acid change {P11S}. In certain specific embodiments, the binding domains are H2 IE, which comprises the set of amino acid changes {I8T, F12S, L14T, A56V}. kα, and H2 IE containing a set of amino acid changes {W6S, L8T, L34S} k It is β.

[0024] In some embodiments, the binding domain of the major histocompatibility complex protein comprises the alpha 1 and alpha 2 domains of a class I MHC protein, which is provided in a single chain with β2 microglobulin. In some such embodiments, the class I protein is subjected to mutagenesis to select for amino acid changes that enhance the solubility of the single chain polypeptide without altering the peptide binding contacts. In certain specific embodiments, the binding domain is the HLA-A2 alpha 1 and alpha 2 domains that contain the amino acid change {Y84A}. In certain specific embodiments, the binding domain is the H2-L alpha 1 and alpha 2 domains that contain the amino acid change {M31R}. d In one particular embodiment, the binding domains are the HLA-B57 alpha 1, alpha 2, and alpha 3 domains containing the amino acid change {Y84A}.

[0025] The sequence of the peptides is determined by any convenient method of high-throughput sequencing. The sequence can be analyzed using a clustering algorithm, for example by the method disclosed in the examples. The peptides can be analyzed to search human proteins (Uniprot) or patient-specific exomes to score peptides of fixed length using a sliding window. The substitution matrix is ​​created by determining the frequency of all amino acids per peptide position. A cutoff of 0.1% frequency for amino acids at a given position is used. An off may be provided to eliminate noise.

[0026] To determine the statistical significance of peptides, human proteome and exome peptide sets are scored. To calculate p-values ​​for exome peptide sets, percentile scores are calculated in the context of human proteome scores. Uncorrected p-values ​​are 1st percentiles. Bonferroni-corrected p-values ​​are uncorrected p-values ​​multiplied by the number of peptides in the variant set.

[0027] MHC proteins. Major histocompatibility complex proteins (also called human leukocyte antigens, HLA, or H2 locus in mice) are protein molecules expressed on the surface of cells that confer a unique antigenic identity to these cells. MHC / HLA antigens are target molecules recognized by T cells and natural killer (NK) cells as originating from the same source of hematopoietic reconstituting stem cells as immune effector cells ("self"), or from another source of hematopoietic reconstituting cells ("non-self"). Two major classes of HLA antigens are recognized: HLA class I and HLA class II.

[0028] The MHC proteins used in the libraries and methods of the invention can be from any mammalian or avian species, such as primate species, particularly humans, rodents including mice, rats, and hamsters, rabbits, horses, cows, dogs, cats, etc. Of particular interest are human HLA proteins and mouse H-2 proteins. HLA proteins include class II subunits HLA-DPα, HLA-DPβ, HLA-DQα, HLA-DQβ, HLA-DRα, and HLA-DRβ, and class I proteins HLA-A, HLA-B, HLA-C, and β2-microglobulin. Mouse H-2 subunits include class I H-2K, H-2D, H-2L, and class II I-Aα, I-Aβ, I-Eα, and I-Eβ, and β2-microglobulin.

[0029] The MHC binding domain is typically a soluble form of a normally membrane-bound protein. The soluble form is derived from the native form by deletion of the transmembrane domain. Advantageously, the protein is truncated to remove both the cytoplasmic and transmembrane domains. In some embodiments, the binding domain of the major histocompatibility complex protein is a soluble domain of class II alpha and beta chains. In some such embodiments, the binding domain is subjected to mutagenesis to select for amino acid changes that enhance the solubility of the single chain polypeptide without altering the peptide binding contacts.

[0030] An "allele" is one of the different nucleic acid sequences of a gene at a particular locus on a chromosome. One or more genetic differences may constitute an allele. An important aspect of the HLA gene system is its polymorphism. Each gene, MHC class I (A, B, and C) and MHC class II (DP, DQ, and DR), exists in different alleles. The current nomenclature for HLA alleles is described in Marsh et al., 19 ...0, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1999, 1999, 1990, 1991, 1992, 1993 al.:Nomenclature for factors of the HLA System, 2010. Tissue Antigens 75:291-455. For HLA protein and nucleic acid sequences, see Robinson et al. (2011), The IMGT / HLA database. Nucleic Acids Research 39 Suppl 1:D1171-6, specifically incorporated herein by reference.

[0031] The numbering of amino acid residues on the various MHC proteins and variants disclosed herein is done to correspond to the full length polypeptide. The boundaries are determined by examining the MHC peptide binding domains (as determined by examining the crystal structures) for "mini" MHC, as exemplified herein with, for example, I-Ek, H2-Ld, and HLA-DR15. The MHC fragments were designed to be either the ends of the beta2 / alpha2 / alpha3 domains as determined by structure and / or sequence, as well as the ends of the beta2 / alpha2 / alpha3 domains for the "full-length" MHC, as exemplified herein with HLA-A2, -B57, and -DR4.

[0032] In some embodiments, the MHC portion of the construct is an MHC portion depicted in any of SEQ ID NOs: 1 to 6. It will be understood by one of skill in the art that the peptide and linker portions can vary from the sequences provided.

[0033] MHC Context. The function of MHC molecules is to bind pathogen-derived peptide fragments and present them on the cell surface for recognition by appropriate T cells. Thus, T cell receptor recognition can be influenced by the MHC proteins presenting the antigen. The term MHC context refers to the recognition by TCR of a given peptide when it is presented by a specific MHC protein.

[0034] Class II HLA / MHC. Class II binding domains generally include the α1 and α2 domains for the α chain, and the β1 and β2 domains for the β chain. At most about 10 amino acids of the transmembrane domain are included, usually at most about 5, and preferably none are included. The deletion is such that it does not interfere with the ability of the α2 or β2 domains to bind peptide ligands.

[0035] In some embodiments, the binding domain of the major histocompatibility complex protein is a soluble domain of the class II alpha and beta chain. In some such embodiments, the binding domain is subjected to mutagenesis to select for amino acid changes that enhance the solubility of the single chain polypeptide without altering the peptide binding contacts.

[0036] In certain specific embodiments, the binding domain is an HLA-DR allele. HLA-DRA proteins include, but are not limited to, DRA * 01:01:01:01, DRA* 01:01:01:02, DRA * 01:01:01:03, DRA * 01:01:02, DRA * 01:02:01, DRA * 01:02:02, and DRA * The binding domain may be selected from the 01:02:03 binding domain, which may be modified to include the amino acid changes {M36L, V132M} or {F12S, M23K}, depending on whether it is provided in a full-length or mini-allelic context. The HLA-DRA binding domain may be combined with any one of the HLA-DRB binding domains.

[0037] In certain such embodiments, the HLA-DRA allele pairs with the binding domain of an HLA-DRB4 allele. The HLA-DRB4 allele may be selected from publicly available DRB4 alleles.

[0038] In other such embodiments, the HLA-DRA allele pairs with the binding domain of an HLA-DRB15 allele. The HLA-DRB15 allele may be selected from publicly available DRB15 alleles.

[0039] In other embodiments, the class II binding domain is an H2 protein, such as I-Aα, I-Aβ, I-Eα, and I-Eβ. In some such embodiments, the binding domain is an H2 IE protein, which may include the set of amino acid changes {I8T, F12S, L14T, A56V}. k α, and H2 IE, which may contain a set of amino acid changes {W6S, L8T, L34S} k It is β.

[0040] Class I HLA / MHC. For class I proteins, the binding domains are restricted The deletion may include the α1, α2, and α3 domains of class I alleles, including HLA-A, HLA-B, HLA-C, H-2K, H-2D, H-2L, without any deletion, which is associated with β2-microglobulin. Not more than about 10 amino acids, usually not more than about 5 amino acids, and preferably none, of the transmembrane domain are included. The deletion is such that it does not interfere with the ability of the domain to bind a peptide ligand.

[0041] In certain specific embodiments, the binding domain is an HLA-A2 binding domain, for example, including at least the alpha 1 and alpha 2 domains of the A2 protein. * 02:01:01:01~HLA-A * A number of alleles have been identified in HLA-A2, including HLA-02:478, the sequences of which are available, for example, in Robinson et al. (2011), The IMGT / HLA database. Nucleic Acids Research 39 Suppl 1:D1171-6. Among the HLA-A2 allelic variants, HLA-A * 02:01 is the most common. The binding domain may contain the amino acid change {Y84A}.

[0042] In certain specific embodiments, the binding domain is an HLA-B57 binding domain, for example comprising at least the alpha 1 and alpha 2 domains of the B57 protein. The HLA-B57 allele may be selected from publicly available B57 alleles.

[0043] T cell receptor refers to the antigen / MHC-binding heterodimeric protein product of the vertebrate, e.g., mammalian, TCR gene complex, including the human TCR alpha, beta, gamma, and delta chains. For example, the complete sequence of the human beta TCR locus has been sequenced as published by Rowen et al. (1996) Science 272(5269):1755-1762, and the human alpha TCR locus has been sequenced and resequenced, see e.g., Mackelprang et al. (2006) Hum Genet. 119(3):255-66. See the general analysis of the T cell receptor variable gene segment family in Arden, Immunogenetics. 1995;42(6):455-500. Each of these is specifically incorporated herein by reference for the sequence information provided and referenced in the publication.

[0044] The multimerized T cell receptor for selection in the method of the present invention is a soluble protein that contains the binding domain of the TCR of interest, e.g., TCRα / β, TCRγ / δ. The soluble protein can be a single chain, or more usually a heterodimer. In some embodiments, the soluble TCR is modified by the addition of a biotin acceptor peptide sequence at the C-terminus of one of the polypeptides. After biotinylation at the acceptor peptide, the TCR can be multimerized by binding to a biotin binding partner, e.g., avidin, streptavidin, traptavidin, neutravidin, etc. The biotin binding partner can include a detectable label, e.g., a fluorophore, a mass label, etc., or can be bound to a particle, e.g., a paramagnetic particle. Selection of the ligand bound to the TCR can be performed by flow cytometry, magnetic selection, etc., as known in the art.

[0045] Peptide ligands for TCRs are peptide antigens against which an immune response can be generated with a T lymphocyte antigen-specific response. Such antigens include those associated with autoimmune diseases, infectious diseases, foods such as gluten, allergies, or tissue transplant rejection. Antigens also include various microbial antigens found, for example, in infectious diseases, vaccinations, etc., including, but not limited to, viruses, bacteria, fungi, protozoa, parasites, and tumor cells. Tumor antigens include tumor-specific antigens, such as immunoglobulin idiotypes and T cell antigen receptors, oncogenes such as p21 / ras, p53, p210 / bcr-abl fusion products, developmental antigens, such as MART-1 / These include Melan-A, MAGE-1, MAGE-3, the GAGE ​​family, telomerase, etc., viral antigens such as human papillomavirus, Epstein-Barr virus, etc., tissue-specific autoantigens such as tyrosinase, gp100, prostatic acid phosphatase, prostate-specific antigen, prostate-specific membrane antigen, thyroglobulin, α-fetoprotein, etc., and autoantigens such as her-2 / neu, carcinoembryonic antigen, muc-1, etc.

[0046] In the method of the present invention, a library of diverse peptide antigens is created. The peptide ligands are about 8 to about 20 amino acids in length, usually about 8 to about 18 amino acids, about 8 to about 16 amino acids, about 8 to about 14 amino acids, about 8 to about 12 amino acids, about 10 to about 14 amino acids, about 10 to about 12 amino acids. It is understood that a completely random library would result in a vast number of possible combinations. In a preferred method, the diversity is limited in the residues that anchor the peptides to the MHC binding domain, which are referred to herein as MHC anchor residues. The location of the anchor residues in the peptides is determined by the specific MHC binding domain. The diversity can also be limited in other locations informed by binding studies, such as the TCR anchor.

[0047] In some embodiments of the invention, a library of polypeptides or nucleic acids encoding such polypeptides is provided, the polypeptide structure having a polynucleotide composition encoding a polypeptide of the formula: P-L1-β-L2-α-L3-T, where each of L1, L2, and L3 is a flexible linker about 4 to about 12 amino acids in length, including, for example, glycine, serine, alanine, etc., α is an α domain of a class I MHC protein or a soluble form of a class II α MHC protein, β is (i) a β chain of a class II MHC protein or (ii) a soluble form of β2 microglobulin for a class I MHC protein, T is a domain that allows the polypeptide to be tethered to a cell surface, including, but not limited to, yeast Aga2, and P is a peptide ligand, typically a library of various peptide ligands as previously described, comprising at least 10 6 Species, at least 10 7 species, more usually at least 10 8 A variety of different peptide ligands are present in the library.

[0048] Conventional methods of assembling coding sequences may be used. To generate diversity in peptide ligands, a series of polynucleotides are created using randomization, error-prone PCR, mutagenic primers, etc., as known in the art. The library of polynucleotides is typically ligated into a vector suitable for the host cell of interest. In various embodiments, the library is provided as a purified polynucleotide composition encoding a P-L1-β-L2-α-L3-T polypeptide, as a purified polynucleotide composition encoding a P-L1-β-L2-α-L3-T polypeptide operably linked to an expression vector, which vector may be suitable for expression in yeast cells, and as a population of cells comprising a library of polynucleotides encoding a P-L1-β-L2-α-L3-T polypeptide, which population of cells may be yeast cells, and which yeast cells may be induced to express the polypeptide library.

[0049] "Appropriate conditions" shall have a meaning that depends on the context in which the term is used. Thus, when used in connection with T cell receptor binding to a polypeptide of the formula P-L1-β-L2-α-L3-T polypeptide encoding polynucleotide composition, the term shall mean conditions that allow the TCR to bind to the cognate peptide ligand. When used in connection with nucleic acid hybridization, the term shall mean conditions that allow a nucleic acid at least 15 nucleotides in length to hybridize to a nucleic acid having a sequence complementary thereto. When used in connection with contacting an agent with a cell, the term shall mean conditions that allow an agent capable of doing so to contact a cell. "Appropriate conditions" as used herein refers to conditions that allow a cell to enter the body and perform its intended function. In one embodiment, the term "appropriate conditions" as used herein refers to physiological conditions.

[0050] The term "specificity" refers to the proportion of negative test results that are true negative test results. Negative test results include false positive and true negative test results.

[0051] The term "sensitivity" is intended to refer to the ability of an analytical method to detect small amounts of an analyte. Thus, as used herein, a more sensitive method for detecting amplified DNA, for example, can detect small amounts of such DNA better than a less sensitive method can. "Sensitivity" refers to the proportion of expected results that have a positive test result.

[0052] As used herein, the term "reproducibility" refers to the overall ability of an analytical procedure to give the same results when performed repeatedly on aliquots of the same sample.

[0053] Sequencing platforms that may be used in the present disclosure include, but are not limited to, pyrosequencing, sequencing-by-synthesis, single molecule sequencing, second generation sequencing, nanopore sequencing, sequencing by ligation, or sequencing by hybridization. Preferred sequencing platforms are commercially available from Illumina (RNA-Seq) and Helicos (Digital Gene Expression, or "DGE")."Next generation" sequencing methods include, but are not limited to, 1) 454 / Roche, including the methods and apparatus described in Margulies et al., Nature (2005) 437:376-380 (2005), and U.S. Pat. Nos. 7,244,559; 7,335,762; 7,211,390; 7,244,567; 7,264,929; and 7,323,305. 2) those commercialized by Helicos BioSciences Corporation (Cambridge, MA) as described in U.S. Patent Application No. 11 / 167046 and U.S. Patent Nos. 7,501,245; 7,491,498; 7,276,720, and in U.S. Patent Application Publication Nos. US20090061439; US20080087826; US20060286566; US20060024711; US20060024678; US20080213770; and US20080103058; 3) those commercialized by Applied Biosystems (e.g., SOLiD sequencing); 4) those commercialized by Dover Systems (e.g., Polonator G.007 sequencing), 5) those commercialized by Illumina as described in U.S. Patent Nos. 5,750,341; 6,306,597; and 5,969,119, and 6) those commercialized by Pacific Biosciences as described in U.S. Patent Nos. 7,462,452; 7,476,504; 7,405,281; 7,170,050; 7,462,468; 7,476,503; 7,315,019; 7,302,146; 7,313,308, and U.S. Patent Application Publication Nos. US20090029385; US20090068655; US20090024331; and US20080206764. Examples of methods and devices include, but are not limited to, those commercialized by Biosciences. All references are incorporated herein by reference. Such methods and devices are provided herein by way of example and are not intended to be limiting.

[0054] Expression constructs. The peptides disclosed herein or sequences encoding the TCRs disclosed herein can be engineered into expression vectors, such as vaccines. The TCR sequence can be introduced into a cell comprising the TCR gene, for example, using CRISPR technology (see, for example, Eyquem et al. (2017) Nature 543:113-117, Ren et al. (see Ren et al. (2017) Protein & Cell 1-10; Ren et al. (2017) Oncotarget 8(10):17002-17011) can be used to introduce the gene into the site of the endogenous gene.

[0055] Amino acid sequence variants are prepared by introducing appropriate nucleotide changes into the coding sequence as described herein. Such variants represent insertions, substitutions, and / or deletions of the indicated residues. Any combination of insertions, substitutions, and / or deletions may be made to arrive at the final construct, provided that the final construct possesses the desired biological activity as defined herein.

[0056] The nucleic acid encoding the sequence is inserted into a vector for expression and / or integration. Many such vectors are available. For example, the CRISPR / Cas9 system can be directly applied to human cells by transfection with a plasmid encoding Cas9 and sgRNA. Viral delivery of CRISPR components has been extensively demonstrated using lentiviral and retroviral vectors. Gene editing by CRISPR encoded by non-integrating viruses, such as adenovirus and adeno-associated virus (AAV), has also been reported. The recent discovery of smaller Cas proteins allows and enhances the combination of this technology with vectors, such as AAV vectors, which are increasingly successful in terms of their safety profile and efficiency.

[0057] Vector components generally include, but are not limited to, one or more of the following: an origin of replication, one or more marker genes, an enhancer element, a promoter, and a transcription termination sequence. Vectors include viral vectors, plasmid vectors, integrating vectors, etc.

[0058] The sequence may be produced recombinantly as a fusion polypeptide with a heterologous polypeptide, for example with a signal sequence or other polypeptide having a specific cleavage site at the N-terminus of the mature protein or polypeptide. In general, the signal sequence may be a component of the vector, or it may be part of the coding sequence inserted into the vector. The heterologous signal sequence preferably selected is one that is recognized and processed (i.e., cleaved by a signal peptidase) by the host cell. In mammalian cell expression, the native signal sequence may be used, or signal sequences from secreted polypeptides of the same species or closely related species, as well as other mammalian signal sequences, such as viral secretory leaders, for example, herpes simplex gD signal, may be suitable.

[0059] An expression vector may contain a selection gene, also called a selectable marker. This gene encodes a protein necessary for the survival or growth of transformed host cells grown in a selective culture medium. Host cells not transformed with a vector containing the selection gene will not survive in the culture medium. Typical selection genes encode proteins that (a) confer resistance to antibiotics or other toxins, such as ampicillin, neomycin, methotrexate, or tetracycline, (b) complement an auxotrophic deficiency, or (c) supply critical nutrients unavailable from complex media.

[0060] An expression vector contains a promoter that is recognized by the host organism and is operably linked to a coding sequence. Promoters are untranslated sequences located upstream (5') to the start codon of a structural gene (generally within about 100-1000 bp) that control the transcription and translation of the specific nucleic acid sequence to which they are operably linked. Such promoters are typically divided into two classes: inducible and constitutive. Inducible promoters are those that are capable of inducing the transcription of a particular gene in culture. Promoters are those that initiate increased levels of transcription from DNA under their control in response to some change in condition, such as the presence or absence of a nutrient or a change in temperature. A large number of promoters recognized by a variety of potential host cells are well known.

[0061] Transcription from vectors in mammalian host cells can be controlled by promoters obtained, for example, from the genomes of viruses such as polyoma virus, fowlpox virus, adenovirus (such as adenovirus 2), bovine papilloma virus, avian sarcoma virus, cytomegalovirus, retrovirus (such as murine stem cell virus), hepatitis B virus, and most preferably simian virus 40 (SV40), from heterologous mammalian promoters such as the actin promoter, PGK (phosphoglycerate kinase), or immunoglobulin promoters, or from heat shock promoters, provided that such promoters are compatible with the host cell system. The early and late promoters of the SV40 virus are conveniently obtained as an SV40 restriction fragment which also contains the SV40 viral origin of replication.

[0062] Transcription by higher eukaryotes is often increased by inserting enhancer sequences into the vector. Enhancers are cis-acting elements of DNA, usually about 10-300 bp in length, that act on a promoter to increase its transcription. Enhancers are relatively orientation and location independent and have been found 5' and 3' to the transcription unit, in introns as well as within the coding sequence itself. Many enhancer sequences are now known from mammalian genes (globin, elastase, albumin, alpha-fetoprotein, and insulin). Typically, however, enhancers from eukaryotic viruses are used. Examples include the SV40 enhancer on the late side of the replication origin, the cytomegalovirus early promoter enhancer, the polyoma enhancer on the late side of the replication origin, and adenovirus enhancers. Enhancers can be spliced ​​into the expression vector at a position 5' or 3' to the coding sequence, but are preferably located at a site 5' from the promoter.

[0063] Expression vectors for use in eukaryotic host cells also contain sequences necessary for the termination of transcription and for stabilizing the mRNA. Such sequences are commonly available from the 5' and sometimes 3' untranslated regions of eukaryotic or viral DNAs or cDNAs. The construction of suitable vectors containing one or more of the components listed above employs standard techniques.

[0064] Suitable host cells for cloning or expressing the DNA in the vectors herein are the prokaryote, yeast, or other eukaryotic cells described above. Examples of useful mammalian host cell lines include mouse L cells (LM[TK-], ATCC#CRL-2648), SV40 transformed monkey kidney CV1 line (COS-7, ATCC CRL1651), human embryonic kidney lines (293 or 293 cells subcloned for growth in suspension culture), baby hamster kidney cells (BHK, ATCC CCL10), Chinese hamster ovary cells / -DHFR (CHO), mouse Sertoli cells (TM4), mouse kidney cells (CV1 ATCC CCL70), African green monkey kidney cells (VERO-76, ATCC CRL-1 587), human cervical carcinoma cells (HELA, ATCC CCL2), canine kidney cells (MDCK, ATCC CCL34), buffalo rat liver cells (BRL 3A, ATCC CRL1442), human lung cells (W138, ATCC CCL75), human liver cells (Hep G2, HB8065), mouse mammary tumor (MMT060562, ATCC CCL51), TRI cells, MRC5 cells, FS4 cells, and a human hepatoma line (Hep G2).

[0065] The expression vectors can be transfected into host cells, including engineered T cells, etc. The cells may be cultured in conventional nutrient media modified as appropriate for inducing promoters, selecting transformants, or amplifying genes encoding the desired sequences. Mammalian host cells may be cultured in a variety of media. Commercially available media such as Ham's F10 (Sigma), Minimum Essential Medium ((MEM), Sigma), RPMI 1640 (Sigma), and Dulbecco's Modified Eagle's Medium ((DMEM), Sigma) are suitable for culturing host cells. Any of these media may be supplemented as necessary with hormones and / or other growth factors (such as insulin, transferrin, or epidermal growth factor), salts (such as sodium chloride, calcium, magnesium, and phosphates), buffers (such as HEPES), nucleosides (such as adenosine and thymidine), antibiotics, trace elements, and glucose or an equivalent energy source. Any other necessary supplements may also be included at appropriate concentrations known to those of skill in the art. Culture conditions such as temperature, pH, etc. are those previously used with the host cell selected for expression and will be apparent to those of skill in the art.

[0066] A nucleic acid is "operably linked" when it is placed into a functional relationship with another nucleic acid sequence. For example, DNA for a signal sequence is operably linked to DNA for a polypeptide if it is expressed as a preprotein that precedes the secretion of the polypeptide, a promoter or enhancer is operably linked to a coding sequence if it affects the transcription of the sequence, and a ribosome binding site is operably linked to a coding sequence if it is positioned so as to facilitate translation. Generally, "operably linked" means that the DNA sequences being linked are contiguous, and, in the case of a secretory leader, contiguous and in reading phase. Enhancers, however, do not have to be contiguous.

[0067] In the event that the polypeptides or nucleic acids of the present disclosure are "substantially pure", they may be at least about 60% by weight (dry weight) of the biomolecule of interest. For example, the composition may be at least about 75%, about 80%, about 85%, about 90%, about 95%, or about 99% by weight of the biomolecule of interest. Purity may be measured by any suitable standard method, such as column chromatography, polyacrylamide gel electrophoresis, or HPLC analysis.

[0068] In another embodiment of the present invention, an article of manufacture is provided that contains materials useful for treating the conditions described above. The article of manufacture includes a container and a label. Suitable containers include, for example, bottles, vials, syringes, and test tubes. The containers can be formed from a variety of materials, such as glass or plastic. The container holds a composition that is effective for treating the condition and can have a sterile access port (e.g., the container can be an intravenous solution bag, or a vial with a stopper pierceable by a hypodermic needle). The active agent in the composition can be a vector suitable for introducing a sequence into a target cell for expression. A label on or associated with the container indicates that the composition is used to treat the selected condition. Additional container(s) can be provided with the article of manufacture that can hold, for example, a pharma- ceutically acceptable buffer, such as phosphate buffered saline, Ringer's solution, or dextrose solution. The article of manufacture can further include other materials desirable from a commercial and user standpoint, including other buffers, diluents, filters, needles, syringes, and package inserts with instructions for use.

[0069] The term "sequence identity" as used herein in reference to polypeptide or DNA sequences refers to the subunit sequence identity between two molecules. If a subunit position in both of the molecules is occupied by the same monomeric subunit (e.g., the same amino acid residue or nucleotide), then the molecules are identical at that position. The similarity between two amino acid sequences or two nucleotide sequences is a direct function of the number of identical positions. Generally, sequences are aligned so that the highest order match is obtained. If necessary, identity can be calculated using published techniques and widely available computer programs such as the GCS program package (Devereux et al., Nucleic Acids Res. 12:387, 1984), BLASTP, BLASTN, FASTA (Atschul et al., J. Molecular Biol. 215:403, 1990).

[0070] The terms "polypeptide," "protein," or "peptide" refer to any chain of amino acid residues, regardless of its length or post-translation modification (eg, glycosylation or phosphorylation).

[0071] By "protein variant" or "variant protein" or "variant polypeptide" herein is meant a protein that differs from a wild-type protein by at least one amino acid modification. The parent polypeptide can be a naturally occurring or wild-type (WT) polypeptide, or can be a modified version of a WT polypeptide. A variant polypeptide can refer to the polypeptide itself, a composition comprising the polypeptide, or the amino acid sequence encoding it. Preferably, a variant polypeptide has at least one amino acid modification compared to the parent polypeptide, such as about 1 to about 10 amino acid modifications compared to the parent, and preferably about 1 to about 5 amino acid modifications.

[0072] The peptides disclosed herein may be flanked by additional amino acid residues so long as the peptide retains its TCR inducibility. Such peptides may be less than about 40 amino acids, such as less than about 20 amino acids, such as less than about 15 amino acids. The amino acid sequence flanking a peptide consisting of an amino acid sequence selected from the group of SEQ ID NOs: 3-5, 7-9, 12, 15-19, 22, 24, 27-30, 37, 67, and 74 is not limited and may be composed of any type of amino acid so long as it does not inhibit TCR recognition. The amino acid sequence may be modified by substituting one or more amino acids therein. Those skilled in the art will recognize that individual additions or substitutions to an amino acid sequence that change a single amino acid or a small percentage of amino acids will result in the preservation of the properties of the original amino acid side chains, and thus are referred to as "conservative substitutions" or "conservative modifications," and that the modification of the protein will result in a protein with similar function.

[0073] In addition to the above sequence modifications of peptides, peptides can be further linked to other substances as long as they retain TCR binding activity. Substances that can be used include peptides, lipids, sugars and sugar chains, acetyl groups, natural and synthetic polymers, etc. Peptides can contain modifications such as glycosylation, side chain oxidation, or phosphorylation, so long as the modifications do not destroy the biological activity of the peptides described herein. These types of modifications can be carried out to impart additional functions (e.g., targeting and delivery functions) or stabilize the polypeptide.

[0074] For example, it is known in the art to introduce various D-amino acids, amino acid mimetics, or unnatural amino acids that are particularly useful for increasing the in vivo stability of a polypeptide, and this concept can also be incorporated into the present polypeptide. The stability of a polypeptide can be assayed in several ways. For example, peptidases and various biological media such as human plasma and serum are used to test stability (see, for example, Verhoef et al., Eur J Drug Metab Pharmacokin 11:291-302, 1986; III. Preparation of peptides).

[0075] The peptides disclosed herein can be prepared using well-known techniques. For example, Peptides can be prepared synthetically, by recombinant DNA technology, or by chemical synthesis. The peptides disclosed herein can be synthesized individually or as longer polypeptides that contain two or more peptides (e.g., two or more peptides, or a peptide and a non-peptide). The peptides can be isolated, i.e., purified to be substantially free of other naturally occurring host cell proteins and fragments thereof, for example at least about 70%, 80%, or 90% purified.

[0076] As used herein, "parent polypeptide," "parent protein," "precursor polypeptide," or "precursor protein" refers to an unmodified polypeptide that is subsequently modified to generate a variant. A parent polypeptide can be a wild-type (or naturally occurring) polypeptide, or a variant or engineered version of a wild-type polypeptide. A parent polypeptide can refer to the polypeptide itself, a composition that includes the parent polypeptide, or the amino acid sequence that encodes it.

[0077] The terms "recipient," "individual," "subject," "host," and "patient" are used interchangeably herein and refer to any mammalian subject, particularly humans, for whom diagnosis, treatment, or therapy is desired. For purposes of treatment, "mammal" refers to any animal classified as a mammal, including humans, farm animals, and livestock, as well as zoo, sport, or pet animals, such as dogs, horses, cats, cows, sheep, goats, pigs, etc. Preferably, the mammal is a human.

[0078] As used herein, "therapeutically effective amount" refers to the amount of therapeutic agent, such as primed T cells, peptide, or polynucleotide vaccine, injected, sufficient to treat or manage a disease or disorder. A therapeutically effective amount can refer to an amount of therapeutic agent sufficient to delay or minimize the onset of a disease, such as delay or minimize the spread of cancer, or an amount effective to reduce or increase signaling from a receptor of interest. A therapeutically effective amount can also refer to an amount of therapeutic agent that provides a therapeutic benefit in the treatment or management of a disease. Furthermore, a therapeutically effective amount in reference to a therapeutic agent of the present invention refers to an amount of therapeutic agent, alone or in combination with other therapies, that provides a therapeutic benefit in the treatment or management of a disease.

[0079] As used herein, the term "dosing regimen" refers to a set of unit doses (typically more than one) that are administered individually to a subject, typically separated by a period of time. In some embodiments, a given therapeutic agent has a recommended dosing regimen that may involve one or more doses. In some embodiments, a dosing regimen includes multiple doses, each of which is separated from the other by the same length of time, and in some embodiments, a dosing regimen includes multiple doses and at least two different periods that separate the individual doses. In some embodiments, all doses in a dosing regimen are of the same unit dosage. In some embodiments, different doses in a dosing regimen are of different amounts. In some embodiments, a dosing regimen includes a first dose at a first dosage, followed by one or more additional doses at a second dosage that is different from the first dosage. In some embodiments, a dosing regimen comprises a first dosing at a first dosage amount, followed by one or more additional dosings at a second dosage amount equal to the first dosage amount, in some embodiments, the dosing regimen correlates with a desired or beneficial outcome when administered across a relevant population (i.e., is a therapeutic dosing regimen).

[0080] As used herein, the term "cancer" (or "cancerous") or "tumor" refers to a tumor that is characterized by the ability for autonomous growth (e.g., rapid proliferation of cells). The term is used to refer to cells having an abnormal condition or pathology that is characterized by a disease state. Hyperproliferative and neoplastic disease states may be categorized as pathological (e.g., characterizing or constituting a disease state) or they may be categorized as non-pathological (e.g., as a deviation from normal but not associated with a disease state). The term is intended to include all types of cancerous growth or oncogenic processes, metastatic tissues, or malignantly transformed cells, tissues, or organs, regardless of histopathological type or stage of invasion. Pathological hyperproliferative cells occur in disease states characterized by malignant tumor growth. Examples of non-pathological hyperproliferative cells include the proliferation of cells associated with wound repair. The term "cancer" or "tumor" is also used to refer to malignant tumors of various organ systems, including those affecting the lung, breast, thyroid, lymphatic glands and lymphatic tissue, gastrointestinal organs, and genitourinary tract, as well as adenocarcinomas, which are generally considered to include malignant tumors such as most colon cancers, renal cell carcinoma, prostate cancer and / or testicular cancer, non-small cell carcinoma of the lung, cancer of the small intestine, and cancer of the esophagus.

[0081] The term "carcinoma" is art-recognized and refers to malignant tumors of epithelial or endocrine tissues, including cancers of the respiratory system, digestive system, genitourinary system, testicular cancer, breast cancer, prostate cancer, endocrine system cancer, and melanoma. "Adenocarcinoma" refers to carcinomas derived from glandular tissue or in which the tumor cells form recognizable glandular structures.

[0082] Exemplary cancer types include AML, ALL, CML, adrenocortical carcinoma, anal cancer, aplastic anemia, bile duct cancer, bladder cancer, bone cancer, bone metastases, brain tumors, central nervous system (CNS) cancer, peripheral nervous system (PNS) cancer, breast cancer, cervical cancer, childhood non-Hodgkin's lymphoma, colon and rectal cancer, endometrial cancer, esophageal cancer, Ewing's family of tumors (e.g., Ewing's sarcoma), eye cancer, gallbladder cancer, gastrointestinal carcinoid tumors, gastrointestinal stromal tumors, gestational trophoblastic disease, Hodgkin's lymphoma, Kaposi's sarcoma, kidney cancer, laryngeal and hypopharyngeal cancer, liver cancer, lung cancer, pulmonary carcinoid tumors, non-Hodgkin's lymphoma, male breast cancer, malignant These include, but are not limited to, mesothelioma, multiple myeloma, myelodysplastic syndromes, myeloproliferative disorders, nasal and paranasal sinus cancer, nasopharyngeal cancer, neuroblastoma, oral and oropharyngeal cancer, osteosarcoma, ovarian cancer, pancreatic cancer, penile cancer, pituitary tumors, prostate cancer, retinoblastoma, rhabdomyosarcoma, salivary gland cancer, sarcoma, melanoma skin cancer, non-melanoma skin cancer, gastric cancer, testicular cancer, thymic cancer, thyroid cancer, uterine cancer (e.g., uterine sarcoma), transitional cell carcinoma, vaginal cancer, vulvar cancer, mesothelioma, squamous cell or epidermoid carcinoma, bronchial adenoma, choriocarcinoma, head and neck cancer, teratocarcinoma, or Waldenstrom's macroglobulinemia.

[0083] Methods and Compositions Compositions and methods are provided for precisely identifying sets of peptides recognized by T cell receptors in a given MHC context, and antigens obtained from such screening using multiplex methods to simultaneously screen two, three, four, five or more libraries. Thus, the peptide ligands (antigens) identified are about 8 to about 20 amino acids in length, usually about 8 to about 18 amino acids, about 8 to about 16 amino acids, about 8 to about 14 amino acids, about 8 to about 12 amino acids, about 10 to about 14 amino acids, about 10 to about 12 amino acids, and may include any of the peptides provided herein as SEQ ID NOs: 1-257.

[0084] Selection of peptides that bind to the TCR of interest is performed by combining the multimerized TCR with a population of host cells expressing the library. The multimerized T cell receptor for selection is a soluble protein that contains the binding domain of the TCR of interest, e.g., α / β, TCRγ / δ, and can be synthesized by any convenient method. The TCR can be a single chain or a heterodimer. In some embodiments, the soluble TCR is modified by the addition of a biotin acceptor peptide sequence at the C-terminus of one of the polypeptides. After biotinylation at the acceptor peptide, the TCR binds to the biotin-binding partner. The biotin binding partner may be multimerized by binding to a biotin-binding protein, such as avidin, streptavidin, traptavidin, neutravidin, etc. The biotin binding partner may contain a detectable label, such as a fluorophore, mass label, etc., or may be bound to a particle, such as a paramagnetic particle. Selection of ligands bound to the TCR may be performed by flow cytometry, magnetic selection, etc., as known in the art.

[0085] Rounds of selection are performed until the selected population has a signal above background, usually at least three rounds and more usually at least four rounds of selection are performed. In some embodiments, the first round of selection is performed with TCRs conjugated to a magnetic reagent, such as superparamagnetic microparticles, which may be referred to as "magnetized", for example, until there is a signal above background. Molday (US Pat. No. 4,452,773), incorporated herein by reference, describes the preparation of magnetic iron-dextran microparticles and provides an overview describing various means of preparing particles suitable for attachment to biological materials. A description of polymer coatings for magnetic particles used in high gradient magnetic separation (HGMS) methods can be found in US Pat. No. 5,385,707. A method for preparing superparamagnetic particles is described in US Pat. No. 4,770,183. Microparticles are usually less than about 100 nm in diameter and usually greater than about 10 nm in diameter. The exact method for conjugation is not critical to the practice of the invention, and several alternatives are known in the art. Direct conjugation attaches the TCR to the particle. Indirect conjugation can be achieved by several methods. The TCR can be conjugated to a particle attached to one member of a high affinity binding system, e.g., biotin, and to another member, e.g., avidin. Alternatively, a secondary antibody that recognizes a species-specific epitope of the TCR, e.g., anti-mouse Ig, anti-rat Ig, etc., can be used. The indirect conjugation method allows the use of a single magnetically conjugated entity, e.g., antibody, avidin, etc., with multiple separate antibodies.

[0086] Alternatively, in a preferred embodiment for the final round of selection, the TCR is multimerized to a reagent with a detectable label, e.g., for flow cytometry, mass cytometry, etc. For example, FACS sorting can be used to increase the concentration of cells with peptide ligands that bind to the TCR. Techniques include fluorescence-activated cell sorters, which can have various degrees of sophistication, such as multicolor channels, low-angle and blunt light scattering detection channels, impedance channels, etc.

[0087] After the final round of selection, polynucleotides are isolated from the selected host cells, and the sequences of the selected peptide ligands are determined, usually by high-throughput sequencing. The selection process is shown herein to result in the determination of a set of peptides bound by TCRs in a specific HLA context. The biological activity of these ligands in activating T cells is verified. The set of selected ligands provides information about the amino acid position constraints required for binding to T cell receptors. Usually, multiple peptide ligands are selected, for example up to 10, up to 100, up to 500, up to 1000, or more different peptide sequences.

[0088] The sequence data from this selected set of peptide ligands provides information about the amino acid constraints at each position of the peptide ligand. This can be shown graphically. The constraints can be particularly relevant at residues that contact the TCR. The data on the amino acid constraints at the peptide positions is input to design a search algorithm for the analysis of the public database. The result of the search provides a set of peptides that meet the criteria of binding to the TCR in an MHC context. The search algorithm is usually embodied as a program of instructions executable by a computer and is implemented by a software component that is installed on the computer.

[0089] Peptides and T cell receptors identified by these methods can be used in vaccine methods, in screening methods to classify patient T cell populations, to prime T cells in vitro, etc.

[0090] In some embodiments, the composition comprises one or more peptides that elicit an immune response against cancer cells, such as colorectal cancer cells, in subjects with at least one HLA allele that is HLA-A2.In another aspect, the present invention provides a composition comprising one polynucleotide that encodes one peptide disclosed herein.In some embodiments, the composition comprises multiple (i.e., two or more) polynucleotides that encode multiple peptides disclosed herein.In some embodiments, the composition comprises one polynucleotide that encodes multiple peptides disclosed herein.

[0091] In a related aspect, a method is provided for treating cancer (e.g., reducing tumor cell growth, promoting tumor cell death) by administering to an individual the peptides disclosed herein or the polynucleotides encoding the peptides.In a related aspect, an isolated primed T cell is provided, which is primed with the peptides disclosed herein.In another aspect, an antigen-presenting cell is provided, which comprises a complex formed between an HLA antigen and the peptides disclosed herein.In some embodiments, the antigen-presenting cell is isolated.

[0092] The term "vaccine" (also called immunogenic composition) refers to a substance that functions to induce anti-tumor (or anti-pathogen) immunity upon inoculation into an animal.

[0093] The cancers that are the subject of treatment by pharmaceutical agents are not limited, and include all types of cancers in which the proteins corresponding to the peptides identified herein are expressed in the subject.Exemplary cancers are carcinomas, such as colorectal cancer.

[0094] If necessary, pharmaceutical agents composed of either peptides or polynucleotides encoding peptides can optionally contain other therapeutic substances as active ingredients, so long as the substances do not inhibit the TCR stimulating effect of the peptide of interest. For example, the formulation can contain anti-inflammatory agents, analgesics, chemotherapeutic agents, etc. In addition to including other therapeutic substances in the pharmaceutical itself, the pharmaceutical can also be administered sequentially or in parallel with one or more other pharmacological agents. The amount of pharmaceutical agent and pharmacological agent depends, for example, on what type of pharmacological agent(s) is / are used, the disease being treated, and the schedule and route of administration.

[0095] The peptides may be directly administered as pharmaceutical agents that are formulated by conventional formulation methods, if necessary. In such cases, in addition to the peptides, carriers, excipients, and those commonly used in drugs may be included as necessary, without being limited thereto. Examples of such carriers include sterile water, physiological saline, phosphate buffer, culture medium, etc. In addition, the pharmaceutical agents may contain stabilizers, suspensions, preservatives, surfactants, etc., if necessary. The pharmaceutical agents may be used to treat and / or prevent cancer.

[0096] Peptides can be prepared in combination, including two or more of the peptides disclosed herein, to stimulate T cells in vivo.Peptides can be in a cocktail state, or can be conjugated to each other using standard techniques.For example, peptides can be expressed as a single polypeptide sequence.The peptides in the combination can be the same or different.By administering peptides, the peptides can be expressed by the HL of antigen-presenting cells. The peptides are presented at high density on the A antigen, and then T cells that specifically react to the complex formed between the presented peptide and the HLA antigen are stimulated. Alternatively, antigen-presenting cells that have peptides fixed on their cell surface can be obtained by extracting dendritic cells from a subject, stimulated with peptides, and then re-administered to the subject the peptide-loaded dendritic cells to stimulate endogenous T cells in the subject, resulting in increased aggression against target cells.

[0097] Pharmaceutical agents containing the peptides described herein as active ingredients may optionally contain adjuvants to effectively establish cellular immunity, or they may be administered together with other active ingredients, and they may be administered by formulation into granules. Adjuvants refer to compounds that enhance the immune response to a protein when administered together (or sequentially) with a protein having immunological activity. Adjuvants that may be applied include those described in the literature. Exemplary adjuvants include, but are not limited to, aluminum phosphate, aluminum hydroxide, alum, cholera toxin, salmonella toxin, and the like.

[0098] In addition, liposome preparations, granule preparations in which peptides are bound to beads of several mcm diameter, and preparations in which lipids are bound to peptides can be advantageously used.Alternatively, intracellular vesicles called exosomes are provided, which present the complex formed between peptides and HLA antigens on their surface.Exosomes can be inoculated as vaccines, just like peptides.

[0099] In some embodiments, the pharmaceutical agents disclosed herein include components that prime T lymphocytes. Lipids have been identified as agents that can prime CTLs in vivo against viral antigens. For example, palmitic acid residues can be attached to the epsilon- and alpha-amino groups of lysine residues and then linked to peptides disclosed herein. The lipidated peptides can then be administered directly, either in micelles or particles, incorporated into liposomes, or emulsified in adjuvants. As another example of lipid priming of CTL responses, E. coli lipoproteins such as tripalmitoyl-S-glycerylcysteine ​​lyseryl-serine (P3CSS) can be used to prime CTLs when covalently attached to an appropriate peptide (see, e.g., Deres et al., Nature 342:561, 1989).

[0100] The method of administration may be oral, intradermal, subcutaneous, intravenous injection, etc., and systemic administration or local administration near the target site finds application. Administration may be performed by single administration, or may be boosted by multiple administrations. The dose of the peptide may be appropriately adjusted according to the disease to be treated, the age and weight of the patient, the method of administration, etc., and is usually 0.001 mg to 1000 mg, for example 0.001 mg to 1000 mg, for example 0.1 mg to 10 mg, and may be administered once every few days to once every few months. Those skilled in the art can appropriately select the appropriate dose.

[0101] The pharmaceutical agents disclosed herein may also include nucleic acids encoding the peptides disclosed herein in an expressible form. As used herein, the phrase "in an expressible form" means that the polynucleotide, when introduced into a cell, is expressed in vivo as a polypeptide that stimulates anti-tumor immunity. In one embodiment, the nucleic acid sequence of the polynucleotide of interest includes regulatory elements necessary for expression of the polynucleotide in a target cell. The polynucleotide(s) may be deployed to stably insert into the genome of the target cell (see, for example, Thomas KR & Capecchi MR, Cell 51:503 for a description of homologous recombination cassette vectors). 12, 1987). See, e.g., Wolff et al., Science 247:1465-8, 1990, U.S. Patent Nos. 5,580,859; 5,589,466; 5,804,566; 5,739,118; 5,736,524; 5,679,647, and WO 98 / 04720. Examples of DNA-based delivery techniques include "naked DNA", facilitated (bupivacaine, polymer, peptide-mediated) delivery, cationic lipid complexes, and particle-mediated ("gene gun") or pressure-mediated delivery (see, e.g., U.S. Patent No. 5,922,687).

[0102] The peptides disclosed herein can also be expressed by viral or bacterial vectors. Examples of expression vectors include attenuated viral hosts, such as vaccinia or fowlpox. This approach involves the use of vaccinia virus, for example, as a vector to express a nucleotide sequence encoding the peptide. Upon introduction into the host, the recombinant vaccinia virus expresses the immunogenic peptide, thereby eliciting an immune response. Vaccinia vectors and methods useful in immunization protocols are described, for example, in U.S. Pat. No. 4,722,848. Another vector is BCG (bacillus Calmette-Guerin). BCG vectors are described in Stover et al., Nature 351:456-60, 1991. A wide variety of other vectors useful for therapeutic administration or immunization are evident, such as adeno- and adeno-associated viral vectors, retroviral vectors, Salmonella typhi vectors, detoxified anthrax toxin vectors, and the like. See, e.g., Shata et al., Mol Med Today 6:66-71, 2000; Shedlock et al. J Leukoc Biol 68:793-806, 2000; Hipp et al., In Vivo 14:571-85, 2000.

[0103] The method of administration may be oral, intradermal, subcutaneous, intravenous injection, etc., and systemic administration or local administration near the target site finds use. Administration may be performed by a single administration or may be boosted by multiple administrations. The dose of the polynucleotide in a suitable carrier, or the dose of the cells transformed with the polynucleotide encoding the peptide, may be appropriately adjusted according to the disease to be treated, the age and weight of the patient, the method of administration, etc., and is usually 0.001 mg to 1000 mg, for example 0.001 mg to 100 mg, for example 0.1 mg to 10 mg, and may be administered once every few days to once every few months. Those skilled in the art can appropriately select the appropriate dose.

[0104] Also provided is an antigen-presenting cell (APC), which presents the complex formed between the HLA antigen and the peptide on its surface. The APC can be obtained by contacting the peptide or a nucleotide encoding the peptide, prepared from a subject that is a target for treatment and / or prevention, and can be administered as a vaccine alone or in combination with other drugs, including peptides, exosomes, or cytotoxic T cells. The APC is not limited to any type of cell, but includes dendritic cells (DCs), Langerhans cells, macrophages, B cells, and activated T cells, all of which are known to present protein antigens on their cell surface for recognition by lymphocytes. DCs are representative APCs with the strongest CTL-inducing activity among APCs, and therefore find particular use as APCs.

[0105] For example, APCs can be obtained by inducing dendritic cells from peripheral blood monocytes and then contacting (stimulating) them with peptides in vitro, ex vivo, or in vivo. When a peptide is administered to a subject, APCs having the peptide immobilized thereon are stimulated within the subject's body. "Inducing APCs" includes contacting (stimulating) cells with a peptide or a nucleotide encoding the peptide to present a complex formed between an HLA antigen and the peptide on the surface of the cell. Alternatively, the peptide can be administered to a subject. After being fixed to APC, APC can be administered to a subject as a vaccine. For example, ex vivo administration can include: a: collecting APC from a subject; and b: contacting the APC of step a with a peptide. The APC obtained by step b can be administered to a subject as a vaccine.

[0106] Such APC can be prepared by a method comprising transferring a gene comprising a polynucleotide encoding a peptide into APC in vitro.The transferred gene can be in the form of DNA or RNA.Regarding the method of transfer, it is not particularly limited, and various methods conveniently performed in the art, such as lipofection, electroporation, and calcium phosphate method, can be used.

[0107] Cells can be engineered to express the TCR provided herein or to respond to the peptide antigen provided herein.Several different cell types are suitable for engineering, particularly T cells or NK cells.In some embodiments, the cells for engineering are autologous.In some embodiments, the cells are allogeneic.

[0108] T cells stimulated against any of the peptides disclosed herein can be used as a vaccine similar to the peptides. Thus, the present invention provides isolated T cells stimulated by any of the peptides. Such T cells can be obtained by (1) administering to a subject, or (2) contacting (stimulating) APCs and CD8 positive cells or peripheral blood mononuclear leukocytes from the subject with the peptides in vitro. T cells stimulated by stimulation from APCs presenting peptides can be derived from a subject that is a target of treatment and / or prevention, and can be administered alone or in combination with other drugs, including peptides or exosomes, for the purpose of modulating the effect. The obtained T cells act specifically against target cells that present the peptides, for example the same peptides used for priming. Target cells can be endogenously expressing cells or genetically transfected cells, and cells that present peptides on their cell surface due to stimulation by these peptides can also be targeted for attack.

[0109] In some embodiments, the engineered cells are T cells. The term "T cells" refers to mammalian immune effector cells that can be characterized by expression of CD3 and / or T cell antigen receptors, and which can be engineered to express the TCRs provided herein or stimulated to respond to peptides provided herein. In some embodiments, T cells are naive CD8 + T cells, cytotoxic CD8 + T cells, naive CD4 + T cells, helper T cells, e.g., T H 1. T H 2. T H 9. T H 11. T H 22, T FH , regulatory T cells, e.g. T R 1. Natural T Reg , inducible T Reg , memory T cells, e.g., central memory T cells, T stem cell memory cells (T SCM ), effector memory T cells, NKT cells, and γδT cells. In some embodiments, the engineered cells comprise a complex mixture of immune cells, such as tumor infiltrating lymphocytes (TILs) isolated from an individual in need of treatment. See, e.g., Yang and Rosenberg (2016) Adv Immunol. 130:279-94, "Adoptive T Cell Therapy for Cancer”, Feldman et al (2015) Semin Oncol.42(4):626-39 “Adoptive Cell Therapy-Tumor-Infiltrating Lymphocytes, T-Cell Receptors, and Chimeric Antigen Receptors", Clinical Trial NCT01174121, "Immunotherapy Using Tumor Infiltrating Lymphocytes for Patients With Metastatic Cancer", Tran et al. (2014) Science 344(6184)641-645, "Cancer immunotherapy based See, "Clinical Immunology and Clinical Chemistry: On Immunotherapy for Patients with Epithelial Cancer," in which the T cells are contacted with the peptide in vitro, i.e., where the T cells are then transferred into a recipient.

[0110] Effector cells for the purposes of the present invention may include autologous or allogeneic immune cells with cytolytic activity against target cells, including, but not limited to, tumor cells. Effector cells may be obtained by in vitro manipulation of peripheral blood lymphocytes (PBLs) and then culturing with a combination of cytokines and / or antigens that increase activation. Cells are optionally separated from undesired cells before culturing, before administration, or both. Cell-mediated cytolysis of target cells by immunological effector cells is believed to be mediated by localized exocytosis of cytoplasmic granules that penetrate the plasma membrane of the bound target cells.

[0111] Cytotoxic T lymphocytes (CTLs) reactive to tumor cells are specific effector cells for adoptive immunotherapy and are of interest for engineering by priming with the peptides disclosed herein or for engineering to express the TCRs disclosed herein. Induction and expansion of CTLs is antigen-specific and MHC-restricted.

[0112] T cells harvested from a subject may be separated from the mixture of cells by techniques that enrich for the desired cells, or may be manipulated and cultured without separation. An appropriate solution may be used for dispersion or suspension. Such solutions are typically balanced salt solutions, such as normal saline, PBS, Hank's balanced salt solution, etc., conveniently supplemented with fetal bovine serum or other naturally occurring factors, along with a low concentration, typically 5-25 mM, of an acceptable buffer. Convenient buffers include HEPES, phosphate buffer, lactate buffer, etc.

[0113] Techniques for affinity separation may include magnetic separation using antibody-coated magnetic beads, affinity chromatography, cytotoxic agents such as complement or cytotoxins conjugated to or used in conjunction with monoclonal antibodies, and "panning" using antibodies attached to a solid matrix, such as a plate, or other convenient techniques. Techniques that provide accurate separation include fluorescence-activated cell sorters, which may have various degrees of sophistication, such as multicolor channels, low-angle and blunt light scattering detection channels, impedance channels, etc. Cells may be selected against dead cells by employing dyes associated with dead cells (e.g., propidium iodide). Any technique that is not overly detrimental to the viability of the selected cells may be employed. The affinity reagent may be a specific receptor or ligand for the cell surface molecule described above. In addition to antibody reagents, peptide-MHC antigen and T cell receptor pairs may be used, such as peptide ligand and receptor, effector and receptor molecules, etc.

[0114] The separated cells may be collected in any suitable medium that maintains the viability of the cells, usually with a cushion of serum at the bottom of the collection tube. A variety of media are commercially available and may be used according to the nature of the cells, including dMEM, HBSS, dPBS, RPMI, Iscove's medium, etc., often supplemented with fetal calf serum (FCS).

[0115] The recovered and optionally enriched cell population can be used immediately for genetic modification or can be frozen and stored at liquid nitrogen temperature, thawed and reused. Cells are usually stored in 10% DMSO, 50% FCS, 40% RPMI1640 medium.

[0116] The engineered cells can be injected into a subject by any convenient route of administration, usually intravascularly, in any physiologically acceptable means, although they can be introduced by other routes where the cells can find a suitable site for growth. Usually, at least 1×10 6 At least 1 x 10 cells / kg 7 At least 1 x 10 cells / kg 8 At least 1 x 10 cells / kg 9 At least 1 x 10 cells / kg 10 Cells / kg or more are administered and are usually limited by the number of T cells obtained during harvest.

[0117] The peptides and T cell receptor sequences are also useful in screening assays for patient samples, where a T cell-containing sample from an individual, such as a blood sample, a tumor biopsy sample, a lymph node sample, a bone marrow sample, etc., is analyzed for (i) the presence of T cells comprising a TCR identified herein, and / or (ii) the presence of T cells responsive to the peptides described herein. The determination of the presence of T cells can be made according to any convenient method, such as determining stimulation by measuring proliferation in response to the presence of the peptide in an HLA complex or presented by an APC. The presence of a specific TCR can be determined by sequencing mRNA, sequencing genomic DNA, etc. The presence of T cells responsive to the peptide or with a TCR of interest allows the patient to be assigned to a group, along with the group, that can be treated by vaccination, APC transfer, etc.

[0118] Also provided herein is a software product tangibly embodied in a machine-readable medium, the software product comprising instructions operable to cause one or more data processing devices to perform operations including generating an n×20 matrix from the positional frequencies of selected peptide ligands obtained by the screening method of the present invention, where n is the number of amino acid positions in the peptide ligand library. The cutoff of the amino acid frequency is set, for example, below 0.1, below 0.05, below 0.01, and frequencies below the cutoff are set to zero. A database of sequences, such as a set of human polypeptide sequences, a set of pathogen polypeptide sequences, a set of microbial polypeptide sequences, a set of allergen polypeptide sequences, etc., is searched using an algorithm that uses an n-position sliding window alignment while scoring the product of positional amino acid frequencies from the substitution matrix. Aligned segments containing at least one amino acid whose frequency is below the cutoff are excluded from matching. The results of the search can be output as a data file in a computer-readable medium.

[0119] The peptide sequence results and database search results may be provided in a variety of media to facilitate their use. "Media" refers to a product containing the expression repertoire information of the present invention. The database of the present invention may be recorded on a computer-readable medium, such as any medium that can be read and directly accessed by a computer. Such media include, but are not limited to, magnetic storage media such as floppy disks, hard disk storage media, and magnetic tapes, optical storage media such as CD-ROMs, electronic storage media such as RAM and ROM, and hybrids of these categories such as magnetic / optical storage media. Those skilled in the art can readily see how any of the currently known computer-readable media can be used to create a product that includes a recording of the present database information. "Recorded" refers to the process of storing information on a computer-readable medium using any such method known in the art. Any convenient data storage structure can be selected based on the means used to access the stored information. A variety of data processor programs and formats can be used for storage, such as word processing text files, database formats, and the like.

[0120] As used herein, a "computer-based system" refers to a system that The term "computer-based system" refers to the hardware means, software means, and data storage means used to analyze the information. The minimum hardware of the computer-based system of the present invention includes a central processing unit (CPU), input means, output means, and data storage means. One of ordinary skill in the art can readily appreciate that any one of the currently available computer-based systems is suitable for use in the present invention. The data storage means may include any product that contains a record of this information as described above, or memory access means that can access such a product.

[0121] A variety of structural formats for the input and output means can be used to input and output information in the computer-based systems of the invention. Such a presentation provides one of skill in the art with a ranking of similarities to identify the degree of similarity contained in the test expression repertoire.

[0122] The search algorithm and sequence analysis can be performed by hardware or software, or a combination of both. In one embodiment of the present invention, a machine-readable storage medium is provided, which includes a data storage material encoded with machine-readable data, which can present any of the data sets and data comparisons of the present invention when a programmed machine is used with instructions for using the data. In some embodiments, the present invention is performed in a computer program running on a programmable computer, which includes a processor, a data storage system (including volatile and non-volatile memory and / or storage elements), at least one input device, and at least one output device. The program code is applied to input data to perform the functions described above and generate output information. The output information is applied to one or more output devices in a known manner. The computer can be, for example, a personal computer, a microcomputer, or a workstation of conventional design.

[0123] Each program may be implemented in a high level procedural or object-oriented programming language to communicate with a computer system. However, the programs may be implemented in assembly or machine language, if desired. In either case, the language may be a compiled or interpreted language. Each such computer program may be stored on a general-purpose or special-purpose programmable computer-readable storage medium or device (e.g., a ROM or magnetic diskette) for configuring and operating the computer to perform the procedures described herein when the storage medium or device is read by the computer. The system may also be considered to be implemented as a computer-readable storage medium configured with a computer program, the storage medium so configured operating the computer in a specific and predefined manner to perform the functions described herein.

[0124] Further provided herein is a method for storing and / or transmitting the sequence and other data collected by the methods disclosed herein via a computer. Any computer or computer accessories, including but not limited to software and storage devices, may be utilized to practice the present invention. The sequence or other data may be input directly or indirectly into the computer by a user. In addition, any of the devices that may be used to sequence or analyze DNA or analyze peptide binding data may be linked to a computer such that the data is transferred to the computer and / or a storage device compatible with the computer. The data may be stored on a computer or a suitable storage device (e.g., CD). The data may also be sent from the computer to another computer or data collection location by methods well known in the art (e.g., internet, ground mail, air mail). Thus, the data collected by the methods described herein may be collected at any location or geographic location and sent to any other geographic location. EXAMPLES

[0125] experiment Example 1 Identification of an antigen for an orphan T cell receptor expressed on tumor-infiltrating lymphocytes The immune system can mount T cell responses against tumors, however, the antigen specificity of tumor-infiltrating lymphocytes (TILs) is poorly understood. Given recent findings that TCRs often exhibit strong preferences for their endogenous ligands, we screened for antigens of "orphan" T cell receptors (TCRs) expressed on TILs derived from human colorectal adenocarcinoma using a yeast display library of peptide human leukocyte antigens (pHLA). Four TIL-derived TCRs were highly diverse, including pHLA-A. * The 02:01 library showed strong selection for peptides presented. Three of the TIL TCRs were specific for non-mutated self-antigens, two of which were present in separate patient tumors and shared specificity for non-mutated self-antigens derived from U2AF2. These results indicate that the limited recognition surface of MHC-bound peptides accessible to TCRs contains sufficient structural information to allow reconstruction of the sequence of peptide targets for pathogenic TCRs of unknown specificity. This finding allows facile identification of tumor antigens.

[0126] To date, no direct interaction screening or combinatorial display system has been used to determine the antigen specificity of orphan TCRs. Herein, we tested our methodology with the goal of identifying antigens recognized by TCRs derived from TILs (Figure 1B). We demonstrated that CD8 TCRs in two HLA-A2 homozygous patients with colorectal adenocarcinoma were recognized by TCRs in the same patient. + Single-cell T cell phenotyping and TCR sequencing of TILs were applied to predict candidate antigen targets from the yeast display library selection (Figure 1B). Of the screened TCRs, four TCRs were HLA-A *Peptide targets in the 02:01 library were isolated. Two of these TCRs were highly similar in sequence and had specificity for an overlapping group of peptides, implying a shared antigen specificity. Synthetic peptides isolated from the library stimulated each T cell receptor of interest, in addition to predicted peptides from the Uniprot human reference genome. Surprisingly, three of the four receptors recognized non-mutated self-antigens. This serves as a proof of principle to link T cell immune responses and their clonal TCRs with a direct antigen identification method using a yeast display library. This methodology may serve as a powerful tool to identify novel cancer antigens recognized by immune responses.

[0127] HLA-A * 02:01 Design of yeast display library. HLA-A * The 02:01 allele is very common, occurring in up to 50% of some populations. HLA-A * The binding motifs for peptides presented by HLA-A02 have been well characterized and a few limited clinically relevant TCRs have been identified. For these reasons, we have proposed to identify potential HLA-A02-presenting TCRs. * We created a yeast display library for screening 02:01-restricted T cell receptors (Figure 1A). Individual yeast express random peptides covalently linked to HLA molecules, allowing peptide identification by DNA sequencing (Figure 1C). This pHLA library contains wild-type β-2-microglobulin (B2M) and HLA-A harboring the single point mutation Y84A. * The present invention features an N-terminal peptide library linked to the 02:01 heavy chain (see STAR Methods). To ensure proper presentation of the peptides in the binding groove, the peptide library was designed to match the amino acid usage in P2 and PΩ to that of HLA-A. * The HLA-A codons are restricted to aliphatic hydrophobic residues favored by HLA-A (Figure 1D-F). Elsewhere, NNK codons randomly code for all 20 amino acids to provide an unbiased library. *Because 02:01 typically displays peptides of 8-11 amino acids in length, we created a library of multiple peptide lengths with epitope tags for multiplexed selection ( Although each library has a theoretical nucleotide diversity dictated by the composition and length of the library, the functional diversity of the libraries is limited (Figure 1F). In total, we estimate that approximately 400 million unique peptides ranging from 8 to 11 amino acids are represented in the combined libraries.

[0128] Validation of the library with MART-1 specific DMF5 TCR. HLA-A * To determine whether the 02:01 complex was properly folded to present peptides, we used a "surrogate" TCR with known specificity. * The DMF5 TCR was used, a naturally occurring TCR that recognizes a 10 amino acid sequence (EAAGIGILTV) (SEQ ID NO: 267) derived from the MART-1 melanoma antigen bound to 02:01. * To validate the 02:01 library, a 10-mer heterocytic peptide, ELAGIGILTV (SEQ ID NO: 264), with improved HLA stability, was introduced onto yeast for HLA-A transcription. * 02:01 and stained with both anti-hemagglutinin (HA) antibody and 400 nM tetramerized DMF5 TCR, demonstrating surface expression of the protein complex and proper folding of pHLA (Figure 2A). To confirm that the library could be used to identify the antigen for the DMF5 TCR, HLA-A * The 02:01 10mer library (Figure 1F) was selected by MACS bead multimerized DMF5 TCR (STAR ​​method, see Figure 2B). Samples from the fourth round of selection were sequenced by Sanger sequencing to identify enriched peptides, most of which were found to be highly related to the MART-1 10mer peptide (Figure 2C). Five sequences were matched to HLA-A *They were individually expressed in yeast together with 02:01 and stained with 400 nM DMF5 TCR tetramer to show TCR-specific binding (Figure 2C) and anti-HLA-A * Staining with 02 demonstrated the conformational expression of the complex (Fig. 8A).

[0129] All rounds of yeast display selection with DMF5 TCR were deep sequenced. The library significantly converged to 68 unique peptides by round 3 of selection, of which the top 10 peptides dominated 91.7% of the library (Figure 2D). The most striking observation was that almost all selected peptides had a Gly at P6 (P6G) (Table 1), indicating that P6G provides flexibility to allow a cleft for CDR3β 100F to which the P6G hydrogen binds. * The results were consistent with the 02:01 crystal structure. Deep sequencing revealed two major clusters of peptide sequences (Figure 2E). To clarify these clusters, the reverse Hamming distance, a metric that identifies the number of exact amino acid matches between two peptides, was calculated between all peptides and then clustered by score (Figure 2E, Table 1). The two major clusters diverged at P4-P6, with a central "GIG" motif in 29 peptides (cluster 1) and a central "DRG" ​​motif in 32 peptides (cluster 2). Cluster 1 peptides were used in a search matrix to score potential human peptide targets, a method previously used to predict human antigens from yeast display selection data (PWM 2014). However, the 10-mer library does not allow for an Ala at P2 of the library, so P2A was manually included in the search matrix and matched to the anchor with the lowest frequency, Leu at 16.67%. From this analysis, nine peptides from the human proteome were found to be highly correlated with DMF5 with various probability scores. Notably, the human MART-1 peptide was the most likely to bind to the DMF5 TCR among the nine predicted peptides (Fig. 2F). Using cluster 2, orders of magnitude more peptides were predicted to bind to the TCR (Fig. 8B, 8C, Table 1). However, the DMF5 TCR did not show any off-target toxicity, indicating that this other "DRG" ​​peptide motif may not be physiologically relevant in the immune response of cancer patients in the study. is.

[0130] HLA-A using neoantigen-specific TCR * 02:01 Blind validation of the library. HLA-A can identify antigens for TCRs with unknown antigen specificity * To test the power of the 02:01 library, we screened three TCRs derived from melanoma patients, all with blinded specificity for neoantigens. These antigens were identified by exome sequencing of tumor material, HLA-A * Prediction of neoantigen presentation by 02:01 and peptide-loaded HLA-A * These were independently identified by staining of patient-derived tumor-infiltrating T cells with 02:01 multimers. Three TCRs, labeled NKI1, NKI2, and NKI3, were recombinantly expressed and used to target HLA-A antigens containing all four peptide lengths. * 02:01 Library selected.

[0131] Only selection against NKI2 yielded 400 nM tetramer-positive yeast starting from round 2 of selection, and peptide-HLA-A *Strong binding of the 02:01 library was shown (Figure 3A). All rounds of selection were deep sequenced and the data was then analyzed based on peptide length for each selection round (Table 2). Peptides converged by round 3 of selection and peptides were clustered by inverse Hamming distance (Figure 3B). Selection results for NKI2 showed dramatic similarity in 9mer, 10mer, and 11mer sequences. These peptide sequences share a conserved Glu at P6, P7, and P8 in the 9mer, 10mer, and 11mer sequences, respectively, and the peptides share a positively charged residue at P5 of the 9mer, 10mer, and 11mer. NKI1 and NKI3 did not yield tetramer-positive selected yeast (Figure 3A) and deep sequencing did not show strong peptide selection.

[0132] As part of the blind validation, HLA-A * A list of 127 neoantigens predicted to be presented by 02:01 served as candidate ligands for the NKI2 TCR. The inverse Hamming distance was calculated for each of these 127 potential neoantigen peptides compared to the list of 10-mer synthetic peptides selected by NKI2 (Figure 3C). ALDPHSGHFV (SEQ ID NO: 265), a peptide neoantigen derived from cyclin-dependent kinase 4 (CDK4), had 5 and 6 of 10 positions identical to library peptides Lib-1 and Lib-2, respectively (Figure 3D). CDK4 was correctly identified and confirmed as the neoantigen target of NKI2. The targets of NKI1 and NKI3 could not be unambiguously identified through this blind validation. NKI1 is specific for the same CDK4 neoantigen and NKI3 is specific for the GCN1L1 neoantigen ALLETPSLLL (SEQ ID NO: 268). The reasons for the lack of target identification are discussed below.

[0133] We confirmed that these synthetic peptides isolated from the pHLA library were specifically recognized by NKI2. We next asked whether they could stimulate either NKI1 or NKI2 expressing T cells. We transduced human peripheral blood lymphocytes with either NKI1 or NKI2 and expressed HLA-A antigens carrying each of the top five peptides selected by NKI2. * 02:01 + The peptides were co-cultured with JY cells. Interestingly, all five peptides elicited IFNγ production by NKI2-transduced T cells in a dose-dependent manner (Figure 3F). Moreover, the top selected peptide mimotope ALDSRSEHFM (SEQ ID NO:269) stimulated these cells as potently as the CDK4 neoantigen ALDPHSGHFV itself. The fifth most selected peptide by NKI2 stimulated the NKI1 receptor in a dose-dependent manner, indicating overlapping specificity.

[0134] Single-cell characterization of tumor-infiltrating lymphocytes in colorectal cancer patients. Our ultimate goal is to characterize expanded and cellular infiltrating lymphocytes in patient tumors using a yeast display platform. The goal of this study is to identify peptide ligands for TCRs derived from cytotoxic T cell populations (Figure 1B). Single-cell techniques for analyzing T cells provide a means to individually phenotype single T cells and sequence their paired αβTCRs in a high-throughput manner.

[0135] The present inventors have * We selected patients who were homozygous for the HLA-A 02 allele (Figure 4A), because T cells isolated from the patients were homozygous for the HLA-A 02 allele. * Although this improves the probability of having a receptor restricted to the 02 allele, it does not exclude the possibility that this TCR may have specificity for other classically or non-classically restricted antigens. All HLA loci were typed for both patients without HLA-C (Table 3). HLA-A * 02:01 and HLA-A *02:06 differs only by an F9Y substitution in the β-sheet floor, which is unlikely to affect TCR recognition. These partial alleles have been described to share a subset of peptide antigens that can be presented, although differences may result in distinct patterns of TCR multimer staining in pHLA.

[0136] Both patients were men in their mid-60s with colorectal adenocarcinoma (Figure 4A). + and CD4 + T cell infiltration was analyzed and the overall structure was observed by H&E staining (Figure 9A). + and CD8 + T cells were found in the lamina propria of the colon, but less so in the tumor. For patient B, CD4 + T cells were not abundant in colon tissue, however there was significant CD8 + There was a T cell infiltration.

[0137] From these two patients, several hundred CD8 + T cells were phenotyped and sequenced from the tumor site along with 53 paired sequences from healthy tissue and 709 paired sequences from tumor tissue (Figure 4B). Any clone seen more than once at the tumor site is considered an expanded clone. In both cases, expanded TCR clones were present in the tumor, suggesting antigen-specific expansion. The most expanded TCR clones constituted 12.9% (23 / 178) and 6.67% (35 / 526) of the sequenced population in patient A and patient B, respectively. This level of expansion in the tumor is consistent with the primary liver cancer and CD4 +This is consistent with other reports on T cell repertoire populations in T cell infiltrated colorectal cancer. Since not many T cells were identified from healthy tissue, clones were likely tumor-restricted and were not shared with healthy tissues if either the α or β chains were not shared. For both patients, both the α and β chain sequences showed only minor sequence overlap between tumor and healthy tissue (Figure 4C). This suggests that most TIL T cell clones are enriched and present in tumors as a result of tumor-driven responses, however, due to limited sampling of healthy tissues, we cannot conclude that any TIL TCRs are present exclusively in tumors.

[0138] T cell receptors sequenced from the patients displayed typical CDR3α and CDR3β lengths (Figure 9B). Both patients had a predominance of TRAV8-3, TRAV19 (Figure 9C), and TRBV7-2 (Figure 9D) expression. Unlike T cells from patient A, T cells from patient B were analyzed by index sorting, which allows pairing of cell surface marker expression with transcript expression. When t-distributed stochastic neighbor embedding (t-SNE) was used to separate T cell populations based on cell surface markers and transcriptional profiles, CD8 + and CD4 + T cell populations were separated into major clusters (Figure 9E). For patient B, there was significant intratumoral CD8 + There was a T cell infiltrate, and the majority of cells sampled co-expressed PD-1 and IFNγ along with heterogeneous expression of other cytotoxicity markers, granzyme B, perforin, and TNF-α. + CD8 + It has been suggested that the T cell population is a tumor-reactive population.

[0139] HLA-A *Screening of orphan TCRs in the 02:01 library. Twenty candidate receptors were selected based on local expansion in tumors, cytotoxicity profile (IFNγ, TNFα, perforin, granzyme B), and in some cases common TCR chain usage (Figures 4B, 4D). HLA-A * Of the 20 candidate TCRs screened in the 02:01 library (Table 4), four TCRs, TCR1A and 2A from patient A and TCR3B and 4B from patient B, enriched peptides from the library (Figure 5A). Interestingly, the two receptors, 2A and 3B, isolated from separate patients, express the same TCRα chain and a similar TCRβ chain, which contain the same length CDR3β sequence with five conservative amino acid differences and a central Val residue generated entirely by NP addition (Figure 5B).

[0140] Each TCR is associated with HLA-A * 02:01 library. Each of the four TCRs enriched for the HLA-linked epitope tag expressed by the yeast, whereas the remaining 16 TCRs did not (Figure 5C). For TCR1A, 2A, and 3B, tetramer stained yeast increased progressively over the rounds of selection. However, TCR4B did not stain yeast despite successive enrichment for the 9-mer epitope tag (Figure 5C). The reason for the lack of enrichment of the remaining 16 TCRs is most likely HLA restriction to alternative HLA alleles, with other possibilities explored in the discussion.

[0141] Yeast selected by TCR1A, 2A, 3B, and 4B were deep sequenced (Table 4). For all four TCRs, the convergent sequences from round 3 of selection and the unique peptide sequences were used to generate peptide motifs and identify local hotspots (Figure 6A). Highly similar TCR2A and 3B were selected for related peptide sequences, 11 of which were common to both (Figure 6C). Selection of a common pool of peptides suggests that these TCRs recognize the same antigen. However, there is a significant difference between these two motifs at P6, with an invariant Asn for TCR2A and a predominance of Asn, Glu, and Ser for TCR3B. In general, TCR2A exhibits a broader degree of cross-reactivity selecting 190 unique peptides with positions P1, P4, and P5 allowing more amino acid substitutions than in the 66 unique peptides selected by TCR3B. TCR1A and 4B have quite different motifs, with 15 and 61 unique peptides, respectively, selected in the third round of selection.

[0142] One way to measure the cross-reactivity of T cell receptors is to look at the breadth of amino acid selection allowed at a particular point in a peptide. To do this, we determined the percentage of all amino acids at every point, accounting for peptide enrichment in round 3 (Figure 6B). TCR1A and 3B are relatively specific to their peptide motif, with more rigidity in amino acid preferences per point. In contrast, TCR2A and 4B are more cross-reactive in their specificity, allowing degeneracy at points along the peptide, except for limited anchor residues. Despite the close similarity of amino acid sequences between 2A and 3B, the TCRs exhibit high contrast in cross-reactivity to their peptide shapes. In this respect, pHLA library screening is effective in "gauging" the relative cross-reactivity of TCRs, which may be important for the selection of TCRs for adoptive cell therapy, where limited cross-reactivity may be desirable to limit autoreactivity.

[0143] TCR target prediction from human proteomes and patient exomes. Peptides identified in yeast display selections generate recognition profiles of sequences for each TCR. This information can be used in algorithms to predict stimulatory human antigens, as was done for the DMF5 TCR with 2014PWM. When applying the algorithm to colorectal cancer data, In the previous study, we generated human predictions for TCR2A, but no predictions for TCR1A and TCR3B, and limited predictions for TCR4B. This motivated the development of two additional methods to predict human peptides from selection data: a modified variant of the previous statistical method (2017PWM), and a method utilizing a two-layer convolutional neural network (2017DL) (see STAR Methods). Using data from previous selections with the DR15 library, we tested the accuracy of the 2017PWM and 2017DL algorithms in predicting peptide antigens. MBP was the best prediction with 2017DL for TCR OB1.A12, the second best prediction with 2017PWM, and the second best prediction in both algorithms for TCR OB1.2F3.

[0144] Two additional algorithms were used to score predicted peptides from the human proteome using the UniProt database. For TCR2A and 3B, there were many peptides predicted by multiple algorithms for both TCRs, indicating shared target specificity. Overall, the three algorithms were collectively able to predict from the human proteome for all four TCRs.

[0145] Because patient mutations may generate neo-antigens recognized by T cells, we performed exome sequencing and variant calling to identify potential candidates. In total, 762 PASS variants were identified in patient A and 4,763 PASS variants were identified in patient B, using at least 30x sequencing coverage for both healthy and tumor tissues. Exome peptides were scored by the 2017PWM and 2017DL algorithms, but few were significant across TCRs. One exception was a 21-nucleotide translocation from an intron to exon 7 of the same WDR66 gene, which generated a neo-antigen peptide in patient A, despite having a suboptimal HLA anchor resulting in little, if any, presentation. This resulted in a novel peptide sequence, EYGVSYEW (SEQ ID NO:270), which closely matches the peptide motif for TCR1A from patient A. Overall, the predictions for the four TCRs suggest that three of the four are likely to bind non-mutated self-antigens.

[0146] In vitro target validation of synthetic and predicted human peptides. Both synthetic peptides selected from the library and predicted human peptides from human and / or exomes were targeted to SKW-3 CD8 T cells engineered to express the four TCRs identified from patients. + The peptides were presented by T2 cells, which were used to stimulate the T cell line. Interestingly, all synthetic library peptides selected by TCR1A potently stimulated T cells through CD69 activation (Figure 7A, Figure 10A) and in a dose-dependent manner (Figure 7B). For TCR1A, neither the exome peptide (EYGVSYEW) (SEQ ID NO: 270), nor the anchored modified exome peptide (EMGVSYEM) (SEQ ID NO: 271), nor the human peptide prediction stimulated the cell line (Figure 7A). Although we have identified a strong antigen recognition motif for TCR1A, we have not been able to recover only the mimotope, which is the stimulatory endogenous antigen.

[0147] For the three TCRs, 2A, 3B, and 4B (Fig. 7C-H), we were able to identify stimulatory endogenous antigens. TCR4B was stimulated by the selected synthetic peptide library and also by 6 / 19 of the predicted human peptides, which is consistent with the higher degree of cross-reactivity seen in the yeast selection deep sequencing analysis (Fig. 7G, 7H, Fig. 10D). Interestingly, we found that TCR4B was stimulated by WDR87, a testis-expressed antigen found to be recurrently mutated in colorectal cancer. 1310-1318 (peptide LLEDLDWDV) (SEQ ID NO: 272), and CRISPLD1, a protein expressed in many cancers, does not 82-90 (peptide NMEYMTWDV) (SEQ ID NO: 273) is stimulated by antigens derived from two different putative driver genes. The cysteine-rich secreted protein, antigen 4, and pathogenicity-associated 1 protein (CAP) superfamily includes CRISPLD1, and these proteins are involved in a wide range of functions including ion channel regulation, reproduction, cancer, cell-cell adhesion, etc. Exome analysis revealed that patient B has a mutation at D143Y in CRISPLD1. TCR4B is involved in the CD74 181- 189 Peptide TMETID WKV (SEQ ID NO: 274), FANCI 1104-1112 Peptide VLEEVDWLI (SEQ ID NO: 275), GEMIN4 771-779 Peptide KLEQLDWTV (SEQ ID NO:276), PDE4a 243- 251 Peptide TLEELDWCL (SEQ ID NO: 277) or PD E4b 231- 239 Peptides TLEELDWCL (SEQ ID NO: 277), and KLHL7 506-514 Five other human antigens, including the peptide NVEYYDIKL (SEQ ID NO:278) The true in vivo specificity cannot be clearly identified without additional tumor information.

[0148] Highly similar TCR2A and 3B have distinct stimulatory profiles for selected synthetic peptides (Figures 7C-F, Figures 10B-C). TCR2A cells were stimulated with 4 of the top 5 peptides selected by TCR2A and 4 of the top 5 peptides selected by TCR3B. However, TCR3B cells were stimulated only with 4 of the top 5 peptides selected by its own TCR and none of those selected by TCR2A. These results support the finding that TCR3B is relatively selective compared to TCR2A (Figure 6B). Remarkably, of the 26 human peptides tested from the predictions (Table 6), only one human peptide was found to stimulate T cells bearing either receptor (Figures 6C, 6E). This peptide was MMDFFNAQM (SEQ ID NO: 279), which is a protein involved in the RNA splicing complex, U2AF2. 174-182 U2AF2 is normally expressed in many human tissues and is overexpressed in many cancers, including colorectal cancer, as determined by antibody staining deposited in the Protein Atlas. Indeed, U2AF2 RNA was overexpressed 2.11- and 2.65-fold in tumor tissues than in healthy tissues in patients A and B, respectively (Figure 11A). When human lymphoma, breast, colon, and lung tumor cell lines were examined, U2AF2 RNA was significantly overexpressed compared to patient samples (Figure 11B-C). U2AF2 has been implicated in promoting tumor metastasis in melanoma and is rarely mutated in solid tumors such as chronic myeloid leukemia, myelodysplastic syndrome, and lung adenocarcinoma. U2AF1, a binding partner of U2AF2, is frequently mutated in cancer, and mutations have been shown to enhance RNA splicing and exon skipping, leading to gene dysregulation in vitro. No mutations were found in U2AF2 or U2AF1 in both patients. For TCR2A, which is more cross-reactive compared to TCR3B, the protein TXNDC11 107-115An additional human peptide derived from VLDFQGQL (SEQ ID NO:280) was able to stimulate a receptor not previously described to be involved in cancer but expressed in the colon and many other tissue types.

[0149] The present inventors have * The affinity of TCR2A for peptide MMDFFNAQM (SEQ ID NO:279) presented by 02:01 was determined by surface plasmon resonance to be 110 μM, identifying a bona fide interaction (FIGS. 11D-E). No affinity could be determined for TCR3B. These low affinities were consistent with the single chain MMDFFNAQM-HLA-A * This may partially explain the lack of TCR tetramer staining in yeast expressing 02:01 (SEQ ID NO:281) (Figure 10F-G). These discrepant results of stimulation versus tetramer binding are seen across all TCRs examined (Figure 10E-H). Conversely, MMDFFNAQM-HLA-A * 02:01 (SEQ ID NO:281) tetramer The body was unable to stain SKW-3 cells expressing either TCR2A or TCR3B. Unfortunately, mass spectrometry did not reveal any HLA-A * Tissue samples were not available to confirm peptide presentation by U2AF2. Although we cannot conclusively determine the immune response targeting peptides derived from U2AF2, evidence from yeast display screening, predictive algorithms, and in vitro stimulation identifies this peptide as a potential target. These results serve as proof of principle that the pHLA library can identify the antigen specificity of TCRs, and that shared specificities across two patients were identified. The pHLA library can also correctly distinguish relative cross-reactivity to peptide antigens.

[0150] The fundamental surprising insight from our investigation is that the specificity encoded in the small recognition kernel of MHC-bound peptides visible to the TCR is sufficient to allow the reconstruction of the entire sequence of endogenous peptides to TCRs of unknown specificity. This finding has important implications for the identification of antigens in T cell-mediated diseases. T cells provide an avenue for therapeutic treatment in infectious diseases, autoimmunity, allergy, and cancer. In most of these, we have little information about T cell specificity, especially in humans, due to limited methods. This situation has been advanced by the availability of high-throughput methods to directly obtain TCR sequences ex vivo from single T cells, but we still face the difficult task of determining the peptide ligand(s). Herein, we combine single-cell TCR analysis with a refined version of a yeast display library screening approach to discover novel pHLA specificities in human colorectal adenocarcinoma. This has major implications for our understanding of T cell specificity in cancer and may be applied to other diseases.

[0151] To our knowledge, this is the first example of TCR ligand identification using combinatorial biology screening techniques, where three TCRs were found to be specific for wild-type antigens that play a role in cancer. A single wild-type antigen derived from U2AF2 is likely to be a shared immune response target in 2 / 2 patients investigated. HLA-A * For all TCRs successfully screened in the 02 library, we were able to identify multiple mimotope peptides that stimulated these TCRs, often more potently than the native peptide. Similar to neoantigens, synthetic peptide antigens or mimotopes have utility as DNA, RNA, or peptide vaccines that stimulate specific antigen-specific T cells to generate more immunogenic responses than self-antigens, to which the immune response is more likely to be tolerant.

[0152] The success of predicting cognate tumor antigens from deep sequencing selection data depends on improved and sophisticated search algorithms and patient tissue validation.In addition, screening a large number of TCRs from a given tumor can increase the probability of associating the selection data with cognate antigens, especially when linked to relevant patient data including RNA expression and / or mass spectrometry of eluted peptides.

[0153] Two main applications can be used for this method in immunotherapy: 1) to identify endogenous and mimotope ligands for orphan TCRs, and / or 2) as a means to classify TCRs based on peptide antigen specificity, which allows for the identification of clinical candidate TCRs that recognize antigens shared across patients. Shared TCRs can be either receptors that share similar TCR sequences that could potentially lead to shared antigen specificity, or TCRs that do not have any shared sequence but recognize the same antigen. Such TCRs that recognize shared antigens are particularly useful in engineered T cell or vaccine therapy. As TCR sequencing continues to advance and more TCR sequencing data becomes available, we can infer TCR restriction to patient HLA and common TCR specificity to convergent TCR sequence clusters. This allows us to infer TCR restriction to patient HLA and common TCR specificity to convergent TCR sequence clusters. TCR ligand identification can be more efficiently targeted to influential TCRs with known HLA restriction.

[0154] Unlike other methods that utilize exome data to identify patient-specific neoantigens that may serve as potential targets for T cell immune responses, this method is an unbiased interrogation of the TCR specificity of the current immune response that relies on the physical interaction between the TCR and pHLA. This ligand identification method may be particularly important in cancers that have low mutational burden and where neoantigen targets may be less prevalent compared to wild-type antigens. We have developed a methodology to improve the use of yeast display libraries to deorphanize TCRs that may provide a means to identify clinically important TCRs and novel antigens. We have used HLA-A as a tool for deorphanization of TILs in two patients with colorectal adenocarcinoma. * The 02:01 library was validated. We primarily identified wild-type antigens as targets of these patient immune responses, with shared responses against the wild-type antigens being of potential therapeutic value.

[0155] STAR method Experimental model and subject details Human Subjects. Two male subjects, ages 64 and 66, both with colorectal adenocarcinoma. The Stanford University Institutional Review Board approved all protocols for collection of human tissue and blood. Patient samples were obtained with patient consent from the Department of Pathology at Stanford Hospital. Both patients were HLA typed without HLA-C and had their HLA-A * Selected specifically for 02 allele expression.

[0156] Primary and cell lines. All cells are grown at 37° C. with 5% CO2 unless otherwise stated.

[0157] Human PBMCs were cultured in RPMI complete (ThermoFisher) containing 10% fetal bovine serum (FBS), 2 mM L-glutamine (ThermoFisher), and 50 U / mL penicillin and streptomycin (ThermoFisher). SKW-3 cells are derived from a human T-cell leukemia and were cultured in RPMI complete (ThermoFisher) containing 10% FBS, 2 mM L-glutamine (ThermoFisher), and 50 U / mL penicillin and streptomycin (ThermoFisher). The cells are cultured in RPMI complete containing L-glutamine, and 50 U / mL penicillin and streptomycin. The transduced cells are cultured with additional 1 ug / mL puromycin (ThermoFisher) and 20 ug / mL zeocin (ThermoFisher). T2 cells are used as antigen presenting cells for SKW-3 cells. * EBV-immortalized B cell line cultured in RPMI complete containing 10% FBS, 2 mM L-glutamine, and 50 U / mL penicillin and streptomycin (ThermoFisher). JY cells are an EBV-immortalized B cell line cultured in RPMI complete containing 10% FBS, 2 mM glutamine, and 50 U / mL penicillin and streptomycin. HEK293T cells are grown in DMEM complete containing 10% FBS, 2 mM L-glutamine, and 50 U / mL penicillin and streptomycin (ThermoFisher). FLYRD18 are grown in DMEM complete with 10% FBS and 2 mM glutamine with 50 U / mL penicillin and streptomycin.

[0158] EBY100 yeast cells were cultured in SDCAA, which contains 20 g dextrose, 6.7 g Difco yeast nitrogen source (BD Biosciences), 5 g Bacto casamino acids (BD Biosciences), 14.7 g sodium citrate (Sigma-Aldrich), and 4.29 g citric acid monohydrate (Sigma-Aldrich) per liter of HO at pH 4.5, or SGCA, in which dextrose is replaced by galactose. Yeast are grown in either SDCAA at 30° C. or in SGCAA for protein induction at 20° C. with atmospheric CO2.

[0159] High Five cells are grown in Insect X-press medium (Lonza) with a final concentration of 10 mg / L gentamicin sulfate (ThermoFisher) at 27° C. with atmospheric CO2. SF9 cells are grown in SF900-III serum-free medium (ThermoFisher) with 10% FBS and a final concentration of 10 mg / L gentamicin sulfate at 27° C. with atmospheric CO2.

[0160] Preparation and selection of yeast display libraries. Chemically competent EBY100 yeast (ATCC) was used to generate yeast display libraries as previously reported (Birnbaum et al., 2014). Briefly, DNA-encoded peptide libraries were generated using primers encoding selected codon sets. The anchor positions at P2 and PΩ of the peptides had restricted codon usage to Leu-Met and Leu-Met-Val, respectively, while all other positions allowed NNK codon diversity (Figure 1E, Table 8). Separate length libraries were encoded vectors with different length codon sets and unique epitope tags (8mer-V5 tag, 9mer-myc tag, 10mer-HA tag, 11mer-VSV tag) for multiplexed selection. Peptide / HLA-A on yeast was then expressed using 10-mer 10-mer 15-mer 16-mer 17-mer 18-mer 19-mer 20-mer 21-mer 22-mer 23-mer 24-mer 25-mer 26-mer 27-mer 28-mer 29-mer 30-mer 31-mer 32-mer 33-mer 34-mer 35-mer 36-mer 37-mer 38-mer 39-mer 39-mer 40-mer 41-mer 42-mer 43-mer 44-mer 45-mer 46-mer 47-mer 48-mer 49 ... * 02:01 To present the complex, HLA-A * The heavy chain of 02:01 was modified with a Y84A mutation, and the heavy chain was truncated at S302. This mutation allows an opening for the linker to pass between the C-terminus of the peptide through the end of the peptide binding groove to B2M to generate a single-chain trimer. The transmembrane-truncated heavy chain is linked to an epitope tag linked to the Aga2p protein for yeast display. The diversity of the yeast library was determined after electroporation by colony counting after limiting dilution.

[0161] Yeast were mixed with 10x diversity of individual length libraries and frozen at -80°C in 2% glycerol and 0.67% yeast nitrogen. Libraries were then purified using the SDCAA as needed. They were thawed in pH 4.5, passaged, induced in SGCAA, and then selected using biotinylated soluble TCR conjugated to streptavidin-coated magnetic MACS beads (SAb) (Miltenyi) as previously described (Birnbaum et al., 2014). Briefly, 10x diversity (4x10) of yeast containing libraries of all four lengths was cultured. 9 Yeast (100 cells) were negatively selected with 250 μL SAb in 10 mL PBS + 0.5% bovine serum albumin and 1 mM EDTA (PBE) for 1 h at 4 °C. Yeast were passed through an LS column (Miltenyi) attached to a magnetic stand (Miltenyi) and washed three times. The flow-through was then incubated for 3 h at 4 °C with 250 μL SAb that had been preincubated with 400 nM biotinylated TCR for 15 min at 4 °C. Yeast were again passed through the LS column and the eluate was grown overnight in SDCAA pH 4.5 after an SDCAA wash. Once yeast reached an OD > 2, they were induced in SGCAA with 10% SDCAA for 2-3 days before additional selection. All subsequent selections were performed with 50 μL SAb or TCR-coated SAb in 500 μL PBE. A fourth round was performed using negative selection after 1 hour incubation of yeast with 400nM SA-647 in 500uL PBE, followed by a PBE wash and 20 minutes incubation with 50μL of anti-Alexa647 microbeads (Miltenyi). Positive selection was performed after 3 hours incubation with 400nM SA-647 TCR tetramer, followed by 20 minutes incubation with anti-Alexa647 microbeads. Naive libraries and all rounds of selection were processed for deep sequencing as described below. Each round was monitored with anti-epitope staining after induction and 400nM TCR tetramer staining was completed for 3 hours at 4°C.

[0162] Individual yeast clones isolated from the selections, or competent yeast electroporated with reconstructed peptide-HLA constructs identified from deep sequencing, were stained with 400 nM TCR tetramers labeled with SA-647 or with SA-647 alone in combination with an anti-epitope tag.

[0163] Deep sequencing of pHLA libraries. 5 × 10 per round of selection 7 DNA was isolated from individual yeast strains by miniprep (Zymoprep II kit, Zymo Research). Individual barcodes and random 8-mer sequences were added to the flanking regions of the sequencing products by PCR and amplified for 25 cycles (Table 8). These primers amplified from the signal peptide of the construct to the middle of the sequence of B2M. This was followed by an additional PCR amplification adding Illumina chip primer sequences to generate Illumina P5-Truseq Read 1-(N8)-Barcode-pHLA-(N8)-Truseq Read 2-Illumina P7. Libraries were purified by agarose gel purification, quantified by nanodrop and / or BioAnalyzer (Agilent Genomics), and deep sequenced by Illumina Miseq sequencer using the 2x150 V2 kit for low diversity libraries.

[0164] Expression of soluble TCRs. Each chain of the F5 TCR was expressed separately in E. coli BL21(DE3), purified, refolded, and functionally validated. For all other TCRs, each chain of the TCR was expressed separately using SF9 cells to produce baculovirus in the pAcGP67a vector (BD Biosciences). Both the α and β chains contained the gp67 signal peptide corresponding to TCR Vα or TCR Vβ. Both constructs utilized the polyhedrin promoter to express the TCR V regions with human constant regions truncated with connecting peptides for soluble expression, and with engineered disulfides (Boulter et al., 2003). Both chains expressed either a C-terminal acidic GCN4 zipper-6×His tag or a C-terminal basic GCN4 zipper-6×His tag. All chains containing the acidic zipper contained a biotinylated acceptor peptide. Both chains contained a 3C protease site between the C-terminus of the TCR ectodomain and the GCN4 zipper. DNA was co-transfected with BD baculogold linearized baculovirus DNA (BD Biosciences) into SF9 cells using Cellfectin II (Life Technologies). Virus was produced in 2 mL cultures. Virus was cultured at 1 × 10 6 A more potent virus was generated by passage at a dilution of 1:1000 into a 25 mL culture of 2 × 10 6 The TCR α and β chains were co-titrated at 1000 cells / mL in 2 mL of High Five (Hi5) (ThermoFisher Scientific) cells to generate 1:1 expression dilutions of the TCR α and β chains as determined by SDS-PAGE gels and Coomassie staining. Co-titrations ranged from 1:1000 to 1:250 for each chain.

[0165] Virus was used to express proteins in 1-4 L volumes at 2 x 10 6 Two to three days after infection, the cells were removed and the supernatant was resuspended in 100 mM Contaminants were precipitated by treatment with Tris-HCl pH 8.0, 1 mM NiCl2, and 5 mM CaCl2. The precipitate was removed by centrifugation, and the supernatant was incubated with Ni-NTA resin (Qiagen) for 3 hours at room temperature. Proteins were washed with 20 mM imidazole in 1×HBS pH 7.2, then eluted in 200 mM imidazole in 1×HBS pH 7.2. After buffer exchange in a 30 kDa filter (Millipore) into 1×HBS pH 7.2, proteins were purified with birA ligase, 100 uM biotin, 40 mM bicine pH 8.3, 10 mM ATP, and 10 mM acetic acid. Proteins used for surface plasmon resonance were treated overnight with 3C protease (10ug / mg TCR). Proteins were purified using an AKTA Purifier (GE Healthcare) Superdex 200 column (GE Proteins were purified by size exclusion chromatography using a ELISA kit (Divisional Healthcare). Fractions were isolated and run on SDS-PAGE gels to confirm 1:1 stoichiometry and biotinylation by streptavidin shift. Fractions were pooled, TCR quantified by nanodrop, and frozen at -80°C in 1x HBS buffer pH 7.2 for storage.

[0166] The Stanford University Institutional Review Board approved all protocols for collection of human tissues and blood. Patient samples from two males, aged 64 and 66 years, were obtained with patient consent from the Pathology Department at Stanford Hospital. A portion of the tumor tissue samples was processed for immunohistochemical staining by formalin fixation and paraffin embedding. Tissues were stained with anti-CD4 (clone 1F6, Leica biosystems), anti-CD8 (clone C8 / 144b, Dako), or hematoxylin / eosin. Fresh tumor and healthy samples were processed as previously performed (Han et al., 2014). Briefly, tumor tissues were split and incubated with 10 MM EDTA in PBS for 30 min. Cell suspensions were made, passed through a 10-μM nylon cell strainer (Becton Dickinson), and treated with 0.5 mg / mL type 4 collagenase (Worthington Biochemical) in RPMI with 5% FBS for 30 min. Tissues were sectioned with a blunt-ended 16-gauge needle and syringe. Tumor tissues were isolated by staining for EpCam (clone 9C4, Biolegend) and LIVE / DEAD Fixable Dead Cell Stain kit (Invitrogen), leaving some samples for antibody staining, sorted by FACS using ARIA II (Becton Dickinson), and processed by AllPrep DNA / RNA Mini kit (Qiagen) for DNA / RNA extraction. Otherwise, lymphocytes were enriched by Percoll (GE Healthcare) gradient centrifugation, and cells were frozen in RPMI containing 10% dimethyl sulfoxide and 40% FBS or used immediately for antibody staining. Prior to staining for FACS, lymphocytes were nonspecifically prestimulated with 150ng / mL PMA+1μM ionomycin for 3 hours. Cells were washed with PBS+0.05% sodium azide+2mM EDTA+2% FCS.

[0167] Lymphocytes were stained with anti-CD4 (RPA-T4, BioLegend), anti-CD8 (OKT8, eBiosciences), anti-αβTCR (IP26, BioLegend), anti-TIM3 (F38-2E2, BioLegend), anti-CD28 (CD28.2, BioLegend), anti-CD103 (Ber-ACT8, BioLegend), anti-CCR7 (G043H7, BioLegend), anti-LAG3 (3DS223H, Invitrogen), anti-CD38 (HIT2, BioLegend), anti-CD45RO (UCHL1, BioLegend), and anti-PD1 (EH12.2H7, BioLegend) antibodies. Dead cells were excluded using the LIVE / DEAD Fixable Dead Cell Stain kit (Invitrogen). Cells were sorted by fluorescence-activated cell sorting (FACS) using an ARIA II (Becton Dickinson) directly into One-Step RT-PCR buffer (Qiagen). Patient B samples were analyzed by index sorting. Reactions were amplified using a pooled primer set previously generated (Han et al., 2014), barcoded, pooled for purification by agarose gel purification, and deep sequenced by Illumina Miseq using the 2x250 V2 kit. Data were processed using a custom software pipeline and individual wells were called for CDR3, TCRα and TCRβ variable, junction, and diversity regions using VDJFasta. Data were analyzed using t-SNE to separate cell populations based on T cell transcriptional and phenotypic markers.

[0168] Sequencing and variant calling of patient exomes. DNA extracted from tumor and healthy tissues was used to generate libraries for exome sequencing. 50 ng of DNA from tumor and normal tissues was tailored into Illumina sequencing libraries using Nextera (Illumina). Libraries were pooled and enriched for exonic regions using Roche Nimblegen SeqCap EZ 3.0 (Roche). Paired-end 75 bp reads were generated using Nextseq500. Tumor-specific variants were determined following GATK Best Practices. Briefly, adapters and low-quality bases were trimmed using cutadapt v1.9. Reads were aligned to hg19 using BWA MEM 0.7.12. Duplicates were removed using Picard tools v1.119, followed by indel realignment and base recalibration using reference files downloaded from GATK v3.5 and GATK Resource Bundle 2.8. Median coverage was determined using bedtools v2.25.0. Finally, variants between normal and tumor were determined using mutect2. Manufacturer's instructions were followed for all kits, and default software parameters were used for all pipelines.

[0169] All exome variants were used to generate alternative coding sequences using the Grch37 assembly from Ensembl. Each alternative coding sequence was processed and scored based on the length of the library peptide. Peptides were scored using the 2017PWM and 2017DL algorithms.

[0170] Algorithm development and prediction for human peptides. Deep sequencing results were analyzed as previously done (Birnbaum et al., 2014) with modifications incorporating deconvolution of libraries for different peptide lengths. Different peptide lengths were identified based on the number of amino acids adjacent to the signal peptide and GS linker. Briefly, paired-end reads were determined from deep sequencing results using PandaSeq. Paired-end reads were analyzed by barcode using Geneious version 6 to identify rounds of selection. All nucleotide sequences with less than 10 counts in rounds 3 and 4 of selection, as well as those that differed from another sequence in the round by only one nucleotide sequence, were merged into dominant sequences. Any data with frameshifts or stop codons were removed from further analysis. Sequences were processed using custom perl scripts and shell commands.

[0171] The inverse Hamming distance is the Hamming distance subtracted from the total peptide length, representing the number of shared amino acids between two peptides. They were calculated using Matlab (Mathworks Inc.) by iterating each peptide against all other peptides from the selected round 3 library sequences. The output score produced is the number of matching amino acid positions between peptides. Based on the inverse Hamming distance, peptides were clustered using Cytoscape and cutoffs were determined manually based on peptide similarity. For the DMF5 TCR, clustering was performed and the clusters were used to generate a substitution matrix for prediction without a cutoff for amino acid frequency. For the NKI TCR, the inverse Hamming distance was sufficient to determine neoantigen specificity for the NKI2 TCR. The 2014 PWM model did not produce any prediction results from a list of 127 neoantigens. No clustering was performed on the four colorectal cancer-derived TCRs prior to algorithmic prediction.

[0172] For 2014PWM and 2017PWM, a substitution matrix was generated from round 3 of full selection and used to search human proteins (Uniprot) or patient-specific exomes to score peptides of fixed length using a sliding window. The substitution matrix is ​​generated by determining the frequency of all amino acids per peptide position. DMF5 For all predictions made with 2014 PWM, except those made for the TCR, a cutoff of 0.1% frequency for amino acids at a given position was used to remove noise. A peptide's score is calculated as the product of the amino acid frequencies at each position. 2017 PWM is less stringent than 2014 PWM in that it allows predicted peptides to incorporate amino acids not found in the selected peptides of the library. This prevents discarding peptide sequences that may not have been selected but could potentially be viable peptide solutions.

[0173] Deep learning method 2017DL was created to consider peptides as a set of entities, rather than viewing each individual portion of a peptide as independent of everything else, as previous algorithms do (Figure 12A). Sequencing data, including peptide sequences and round counts, were preprocessed in R to remove any peptide sequences with fewer than 3 counts across all rounds. The data was then normalized by multiplying each round count by the average number of counts across the round, then dividing by the number of counts in a given round. An adapted fitness score was used to score each peptide in the library, derived from a fitness function represented by an exponential curve fitted to each peptide through the normalized round counts (Figure 12B).

[0174] A model was then created using the fitness scores for each peptide, with the peptide represented as a 20×L matrix, where L is the length of the peptide sequence (FIG. 12C). The 20 rows of the matrix relate to the 20 possible amino acids. The amino acids are represented as one-hot vectors, with the vectors containing a single 1 and the rest being 0. The matrix representing the peptides was flattened into a 20×L length feature vector for use in training the neural network. The one-hot matrix was used as input and the fitness scores were used as output. A previously described network architecture utilizing two hidden layer networks with 10 and 5 nodes, respectively, was implemented using data from library peptides (FIG. 12D). Training was performed in Lua using the Torch package. This model was used to score a given peptide from the Uniprot database (downloaded on December 18, 2015) and patient-specific exomes, using peptides isolated from an L-length sliding window that was converted to a one-hot matrix for neural network input. For each peptide from the entire proteome, a p-value was calculated, representing the probability of random selection and a Bonferroni corrected p-value that the peptide had a fitness score as high as or higher than the peptide being scored.

[0175] Measurement of T cell activation in co-culture assays. Four TCRs isolated from colorectal cancer patients, peptides selected from the library, were cloned into the MSCV-based vector pMIG II in the α-P2A-β configuration with wild-type signal peptides of the TCR variable genes and full-length unmodified constant regions. The P2A skip sequence allows 1:1 stoichiometric expression of the TCRs. The MSCV-based vector pMIG II was also used to generate human CD3 in the form δ-F2A-γ-T2A-ε-P2A-ζ. The packaging vector pCL10A was used to incorporate env, gag, and pol to allow human mammalian tropism and virus production. The vectors introduced puromycin and zeocin selectivity to infected cells. Retroviruses were generated for each TCR and human CD3 in human embryonic kidney 293T cells with 5 μg TCR or human CD3 DNA and 3.3 μg pCL10A DNA. X-tre in serum-free DMEM was used. Virus was produced using meGENE 9 DNA transfection reagent (Sigma-Aldrich). In cell culture, cells were harvested with 2% FBS DMEM and the medium was changed at 12 hours. Virus was harvested at 36, 40, 44, and 48 hours in 2.5 mL volumes each to be pooled, filtered through a 0.45 μM syringe filter (Fischer Scientific), frozen at -80°C, or used immediately to express TCR. - CD8 + SKW-3 cells were infected with 2 mL virus for TCR and 2 mL virus for human CD3 by spinning at 2500 rpm for 2 hours at 32°C, using 5ug / mL polybrene (Millipore) to infect 2x10 610 SKW-3 cells were co-infected with 10 ng / mL IgG. Virus was removed, replaced with medium, and cells were cultured. Transduced SKW-3 cells were cultured indefinitely after 2-3 days in 20ug Zeocin and 1ug Puromycin to select for TCR and human CD3 co-expression. Cells were then co-stained for TCR (IP26, BioLegend) and human CD3 (UCHT1, BioLegend) and sorted on an SH800 cell sorter (Sony Biotechnology Inc.).

[0176] Transduced SKW-3 cells were co-cultured with TAP-deficient T2 cells at a 2:1 ratio with various peptide dilutions. The top 5 synthetic peptides isolated from yeast display selection were tested along with predictions determined from the three prediction algorithms. Peptides were synthesized to >70% purity (Genscript) (Elim Biopharm), resuspended at 20 mM in dimethylsulfoxide, and stored at -20°C. CD69 (FN50, BioLegend) was measured at 18 hours to detect early T cell activation by flow cytometry using Accuri C6 (BD Biosciences). SKW-3 T cells were detected by UCHT1 staining and checked for TCR and CD3 expression. T2 cells were probed for HLA-A by antibody (BB7.2, BioLegend). * 02 expression. Data were analyzed using FlowJo version 10 (FlowJo, LLC) and samples were gated by forward and side scatter for SKW-3 cells and for UCHT1+ cells, followed by analysis for CD69 expression. Experiments were performed in biological and technical triplicates. p values ​​were calculated by ordinary one-way ANOVA in Prism and experiments were plotted with either standard deviation or standard error of the mean displayed.

[0177] CDK4-specific TCR clones 10 (NKI1) and 17 (NKI2) ​​were derived from TILs of a melanoma patient and screened using HLA multimers loaded with predicted neoantigens essentially as described. The variable parts of both TCRs were cloned into retroviral vectors encoding the murine TCR α and β constant domains. FLYRD18 packaging cells were cultured at 1.2 × 10 6 Cells were seeded at 10x10 cells / well in 10 cm dishes. One day later, cells were transfected with 10 μg retroviral vector DNA encoding the CDK4 TCR using 25 μl X-tremeGENE HP DNA (Sigma-Aldrich). After 48 h, retroviral supernatants were isolated and transferred to RetroNectin-coated 24-well plates and centrifuged at 430 g for 90 min. PBMCs were activated and selected with anti-CD3 / CD28 beads (ThermoFisher) at a bead-to-cell ratio of 3:1. 48 h after stimulation, T cells were plated at 0.5x10 6 Surface expression of the introduced CDK4 TCR on the transduced T cells was monitored by APC-labeled CDK4 R>L HLA-A in combination with anti-mouse Vβ TCR-PE-labeled antibody (BD Biosciences). * 02:01 tetramer was measured using a FACSCalibur (Becton JY cells were pulsed with the indicated concentrations of CDK4 peptides or predicted peptides for 1 h at 37°C and then washed twice. 6 0.2 × 10 TCR-transduced T cells were cultured in the presence of 1 μL / mL Golgiplug (BD Biosciences). 6 Peptide pulsed T cells were incubated with JY cells loaded with 100% IgG4-immunoglobulin (IgG) and 100% IgG4-immunoglobulin (IgG) ...

[0178] Refolded HLA-A with exogenous peptide * Expression of HLA-A in Rosetta BL21 DE3 E. coli cells using the pet26b vector. * HLA-A (1-275) and β2M (1-100) were expressed separately. The inclusion bodies containing the separate proteins were dissolved in 8 M urea, 40 mM Tris-HCl pH 8.0, 10 mM EDTA, and 10 mM DTT. For in vitro refolding, HLA-A * 02 heavy chain, β2M, and MMDFFNAQM (SEQ ID NO:279) peptide were mixed in a 1:2:10 molar ratio and diluted in refolding buffer containing 0.4M L-arginine-HCl, 100 mM Tris-HCl pH 8.0, 4 mM EDTA, 0.5 mM oxidized glutathione, and 4 mM reduced glutathione. After 72 hours at 4°C, the protein was dialyzed in 10 L of 10 mM Tris-HCl and purified by weak ion exchange using a DEAE cellulose column. The protein eluate was purified using size exclusion chromatography on a Superdex 200 column and ion exchange chromatography on a 5 / 50 Mono Q column (GE Healthcare). After buffer exchange into 1x HBS pH 7.2 on a 30 kDa filter (Millipore) before being run on a size-exclusion Superdex 200 column, the protein was biotinylated overnight at 4°C using birA ligase, 100 uM biotin, 40 mM bicine pH 8.3, 10 mM ATP, and 10 mM magnesium acetate.

[0179] MMDFFNAQM-HLA-A * Surface plasmon resonance to measure TCR2A and 3B binding affinity to 02:01. TCR2A and 3B and MMDFFNAQM-HLA-A * Interaction with 02 (SEQ ID NO:281) was measured by surface plasmon resonance using a BIAcore T100 (GE Healthcare) biosensor at 25°C. Biotinylated MMDFFNAQM-HLA-A2 (SEQ ID NO:282) was immobilized on a streptavidin-coated BIAcore SA chip at approximately 1000 resonance units (RU). A different flow cell was immobilized with a non-related peptide-HLA-A2, which served as a blank control. Various concentrations of either 2A or 3B TCR were run sequentially over the blank and MMDFFNAQM-HLA-A2 (SEQ ID NO:282). TCR injection was stopped after 60 seconds, allowing sufficient time for the SPR signal to reach a plateau. The dissociation constant (K D ) was won.

[0180] Quantitative PCR to determine relative RNA expression of U2AF2. The relative amount of U2AF2 RNA expression was determined using RNA extracted from tumor and healthy patient tissues as previously described. In addition, RNA was extracted from the following cell lines: lymphoma: K562, Daudi, breast: MDA MB 231, lung: A549, EKVX, HCC78, H358, H441, H1373, H1437, H1650, H1792, H2009, H2126, H3122, LC-2 / ad. cDNA was generated in triplicate using the High-Capacity RNA-to-cDNA kit (Thermofisher). cDNA samples were pooled for aliquots and quantitative real-time PCR was performed using TaqMan probes (ThermoFisher), TaqMan Universal Master Mix II, no UNG (ThermoFisher), and the QuantStudio 3 Real-Time PCR System (ThermoFisher). PCR was performed in technical quadruplicate. The U2AF2 probe (ThermoFisher, Hs00200737_m1) amplified a 75 bp region spanning the exons of U2AF2. The 18S RNA probe (ThermoFisher, Hs99999901_s1) was used as a housekeeping gene and a 187 bp region was amplified. The cycle threshold of U2AF2 relative to 18S RNA was calculated for each sample and compared to either Patient A healthy tissue or Patient B healthy tissue cycle threshold to determine relative expression levels. Standard deviations are plotted.

[0181] Quantitative and statistical analysis. T cell stimulation assay with SKW-3 cells. Data were analyzed using Flowjo to determine the T cell stimulation assay for SKW-3 cells and CD3 + The population is gated to identify T cells. T cells are then gated for CD69 expression using a negative control (no peptide). CD3 + Median MFI of CD69 expression and percentage of cells expressing CD69 in the groups are analyzed. Ordinary one-way ANOVA compared to negative control (no peptide) was determined for both analyses using Prism. 100 μM peptide stimulation was completed in biological and technical triplicates. Only one of the biological triplicates is shown. Peptide titration experiments were performed in biological triplicates. All biological triplicates were analyzed collectively. Legends for p-value designations are provided for each figure. Either SEM (n=3, technical triplicates) or SD (n=3, biological triplicates) was used and are provided in the corresponding figure legends.

[0182] 2014 PWM Scoring. Scoring is performed as presented in (Birnbaum et al., 2014). A frequency matrix is ​​created from the round 3 selection data using the sequencing read count as a multiplier to the peptide sequence. Each position in the peptide is multiplied by the read count to get a count of the number of times a given amino acid occurs. This is done for each unique peptide in round 3, dividing the amino acid count per position by the number of total reads. The frequency matrix is ​​then used to score every Nmer peptide in the human proteome, where N is the length of the selected peptide from the library. Scoring is performed by multiplying by the frequency of a given amino acid across the peptide.

[0183] 2017PWM and 2017DL peptide scoring. The algorithms were developed in this paper. For both 2017PWM, a frequency matrix is ​​developed as in 2014PWM, except that an additional frequency matrix is ​​developed for data across all rounds of selection, not just round 3. The ratio per site per amino acid is taken as the round 3 frequency matrix versus the full round frequency matrix. A pseudocount frequency of 0.05 is performed for zero values, and the log10 of the ratio is taken. This score is interpreted as the enrichment ratio of a particular amino acid at the site. This score is used to determine the overall enrichment of a given peptide from the exome or human proteome by multiplying the score for each site. The 2017DL algorithm is performed as described in the methods.

[0184] To determine the statistical significance of peptides, human proteome and exome peptide sets are scored. To calculate p-values ​​for exome peptide sets, percentile scores are calculated in the context of human proteome scores. Uncorrected p-values ​​are 1st percentiles. Bonferroni-corrected p-values ​​are uncorrected p-values ​​multiplied by the number of peptides in the variant set.

[0185] Quantitative PCR analysis. Quantitative PCR was performed on technical quadruplicate samples. The relative expression level of U2AF2 RNA to 18S RNA (delta cycle threshold) was calculated by subtracting the cycle threshold. The fold change compared to healthy (delta delta cycle threshold) was determined by subtracting the relative cycle threshold of the reference to the sample (delta cycle threshold). The standard deviation of the delta cycle threshold is calculated using the following formula: , s = standard deviation, s1 = standard deviation of the target sample, and s2 = standard deviation of the reference sample. The delta-delta cycle threshold standard deviation utilizes the standard deviation of the delta cycle threshold test sample.

[0186]

number

[0187] Data and software availability. Exome sequencing. Data are available in the short read archive under BioSample accessions SAMN07350021, SAMN07350022, SAMN07350023, SAMN07350024, SAMN07350025, SAMN07350026, SAMN07350027, SAMN07350028, SAMN07350029, SAMN07350030, SAMN07350031, and SAMN07350032.

[0188] Deep sequencing. Data are available in the short read archive under BioSample accessions SAMN07977164, SAMN07977165, SAMN07977166, SAMN07977167, SAMN07977168, and SAMN07977169.

[0189] [Table 1-1]

[0190] [Table 1-2]

[0191] [Table 1-3]

[0192] Sequences identified from round 3 deep sequencing of the DMF5 10mer library selection after clustering by inverse Hamming distance. These clusters were used to perform predictions against the Uniprot database using 2014PPM. Nine predictions for the "GIG" cluster and the top 10 predictions for the "DRG" ​​cluster are listed.

[0193] [Table 2-1]

[0194] [Table 2-2]

[0195] [Table 2-3]

[0196] Sequences identified from round 3 deep sequencing of NKI2 library selection listed by peptide length. Related to Figure 3.

[0197] [Table 3]

[0198] [Table 4-1]

[0199] [Table 4-2]

[0200] HLA-A * TCR screened against the 02:01 library. TCR sequences were selected based on clonality in tumors, phenotypic profile, exclusivity to tumors, and additionally by associated TCR sequences. Numbers under the tumor and healthy labels indicate the number of times the paired TCR sequence was seen from this tissue. Related to Figures 5 and 6.

[0201] [Table 5-1]

[0202] [Table 5-2]

[0203] [Table 5-3]

[0204] TCR2A: TCR consisting of TRAV19, TRAJ32, CDR3: (SEQ ID NO: 261) CALSEARGGATNKLIF, and TRBV10-1, TRBJ1-1, CDR3: (SEQ ID NO: 262) CASSRDTVNTEAFF

[0205] [ka]

[0206] [ka]

[0207] TCR3B: TCR consisting of TRAV19, TRAJ32, CDR3: (SEQ ID NO: 261) CALSEARGGATNKLIF, and TRBV10-1, TRBJ2-7, CDR3: (SEQ ID NO: 263) CASSRDFVSNEQYF The same alpha as TCR2A

[0208] [ka]

[0209] cross reference This application claims the benefit of U.S. Provisional Patent Application No. 62 / 476,575, filed March 24, 2017, which is incorporated herein by reference in its entirety.

Claims

1. A peptide comprising:

13. As substantially shown in the drawings and substantially described in the specification peptide.

Images